An Integrated Model of Buyer-Seller Relationships in the Australian Wine Industry
Major thesis submitted in partial fulfilment of the requirements for the degree of
Doctor of Philosophy in Sciences
Simon Alexander Somogyi
School of Agriculture, Food and Wine
University of Adelaide
Australia
February 2012
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Abstract
The study examined how communication elements and relational norms such as power asymmetry influence relationship quality from the perspective of grape growers in their relationships with wineries using an integrated model of the relationship between the two actors (grape grower and winery) in the Australian wine industry.
First, a review of the literature identified a deficiency of research examining communication between grape growers and wineries and the effect that power asymmetry has on relationship quality. The literature review also identified that relationship quality is measured both uni-dimensionally and multi-dimensionally. Second, a qualitative exploratory study, involving in-depth interviews with grape growers, examined how dimensionality of collaborative communication and power asymmetry in the relationship (favouring the winery) influenced relationship quality. Furthermore, the elements of collaborative communication were found to influence the relationship quality, in particular the modality, formality, directionality and the non- coercive abilities of communication. The exploratory study, combined with the literature review, created a conceptual model based on a multidimensional measurement of relationship quality and an alternative conceptual model based on a uni-dimensional measurement.
Finally, the study involved a questionnaire administered to grape growers to test quantitatively the conceptual models. The conceptual models were tested via Structural Equation Modelling using Partial Least Squares Regression. The main results showed that direct modes of communication (for example, face to face and direct email communication) positively affected relationship quality, while non-direct modes (such as seminars and newsletter) negatively affected relationship quality, and that the power asymmetry led to decreased grape prices and lower relationship quality. The linkages in the main conceptual model between satisfaction (an element of relationship quality), and many of the relational dimensions, were insignificant. The reason for this was due to the price per tonne that the grape growers received for their produce (grapes). The estimation of the alternative model, based on a uni-dimensional estimation of relationship quality, showed a greater fit of the data with less significant path
ii estimations. Further analysis of the models showed a direct correlation between the relationship quality and price of grape supplied, whereby the higher the price they received, the higher the level of relationship quality they experienced.
The quantitative phase of the study also highlighted three clusters of respondents‟ relationships with wineries.
Firstly, there was an “unsustainable relationship”, whereby the respondents experienced low levels of relationship quality, high power asymmetry favouring the winery, and a very low price per tonne for their grapes. Respondents in this cluster were mainly located in warm climate grape growing regions, and mainly dealt with large, publicly owned wineries.
Secondly, an “OK relationship” was observed, whereby respondents experienced higher levels of relationship quality and lower high power asymmetry favouring the winery than the “unsustainable relationship” cluster. They received a higher price per tonne than the “unsustainable relationship‟ cluster, were located in cool to warm climate grape growing regions, and dealt with more small, privately owned wineries than the “unsustainable relationship” cluster.
Thirdly, there was a “good relationship”, whereby respondents experienced the highest level of relationship quality and the least amount of power asymmetry favouring the winery, of the three clusters. This cluster also received the highest price per tonne of the three clusters and was mostly located in cool climate wine growing regions. This cluster dealt with more small, privately owned wineries than the other two clusters.
Wineries will need to take into consideration the results of this study, particularly the dimensionality of communication and power asymmetry effects, when dealing with grape growers.
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Statement of Declaration
I declare that this thesis does not incorporate without acknowledgement any material previously submitted for the award of any other degree or diploma in any university or other tertiary institution; and that to the best of my knowledge and belief, it does not contain any materials previously published or written by another person, except where due reference has been made in the text.
I give consent to this copy of my thesis, when deposited in the University Library, being made available for loan and photocopying, subject to the provisions of the Copyright Act 1968. I also give permission for the digital version of my thesis to be made available on the web, via the University‟s digital research repository, the Library catalogue, the Australasian Digital Theses Program (ADTP) and also through web search engines, unless permission has been granted by the University to restrict access for a period of time.
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Simon Alexander Somogyi
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Acknowledgements
I would like to acknowledge the following people and parties for their assistance during my study.
Firstly, I would like to acknowledge my supervisors, Dr Elton Li and Assoc Prof Johan Bruwer who provided great advice and encouragement over the duration of the project. It was their encouragement that aided me through the journey. I would also like to thank Dr Amos Gyau who not only gave wise advice and comment but reinvigorated my enthusiasm when things were not working as they should. I consider Amos not only a colleague, but also a friend and confidant.
Secondly, this project would not have been possible without the assistance and advice of many Australian wine industry stakeholders. In particular, I would like to thank Lyndal Sterenberg of Morton Blacketer who not only shared her vast experience, but also gave me access to respondents. I would also like to acknowledge Mark McKenzie of Wine Grape Growers‟ Australia, Mike Stone formerly of the Murray Valley Wine Growers‟ Association, Brian Simpson of the Riverina Wine Grapes Marketing Board, Di Davidson and Sam Burton or Davidson Viticulture, Hamish Franks of Foster Groups, and John Hahn and Elise Hayes of the Barossa Grape and Wine Association who gave advice and access to respondents. Their assistance is greatly appreciated. I would also like to thank the numerous regional grape growers‟ associations, too many to list, who gave access to respondents. Their good humour and willing cooperation toward me and the project was remarkable considering the harsh economic and social issues facing their constituents. They cannot be thanked enough.
I would also like to acknowledge the anonymous grape growers who graciously gave their time and effort assisting in the pilot phases of the study, including the questionnaire design process. These individuals must be commended for their good humour and patience when it appeared that I was bothering them. Thank you all very much.
On a personal note, I would like to thank my mother and father, Lydia and Andrew, and my sister Julia. They constantly encouraged me and were always there during the good and bad times throughout the journey. v
I would also like show my immense appreciation of all the grape growers who participated in this study. This project would not have existed without their participation. I thank you from the bottom of my heart and hope you keep on fighting. I would also like to thank Dr Vic Beasley who professionally edited this thesis.
And lastly I would also like to thank my fiancée, Justine, who not only performed the task of proofreading this document, having to deal with my spelling and grammatical foibles, but also provided me with support and encouragement during the bad times. I cannot thank her enough for what she has given me.
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Table of Contents
Abstract ...... ii
Statement of Declaration ...... iv
Acknowledgements ...... v
Table of Contents ...... vii
Table of Tables ...... xiii
Table of Figures ...... xv
Chapter 1: Introduction ...... 1
1.1 Chapter outline ...... 1
1.2 History of the Australian wine industry ...... 1
1.3 Current state of the Australian wine industry ...... 2
1.4 Research problem and objectives and thesis title ...... 5
1.5 Research Design and significance of the study ...... 7
1.6 Structure of the thesis ...... 10
Chapter 2: Literature Review ...... 11
2.1 Introduction ...... 11
2.2 Australian wine industry context for discussion of literature ...... 11
2.3 Business to business interaction ...... 12
2.3.1 Industrial markets and inter-firm relational development ...... 12
2.4 Business to Business Marketing ...... 14
2.4.1 B2B purchasing ...... 14
2.4.2 Exchange relationships ...... 19
2.4.3 Relationship development and relationship marketing ...... 22
2.4.4 Business to Business networks ...... 24
2.5 Relational norms ...... 28
2.6 Communication ...... 30
2.7 Relationship quality ...... 32 vii
2.7.1 Trust as a dimension of relationship quality ...... 33
2.7.2 Satisfaction as a dimension of relationship quality ...... 35
2.8 Power Asymmetry ...... 36
2.9 Literature Discussion ...... 38
2.10 Chapter conclusion ...... 40
Chapter 3: Exploratory research methodology and results ...... 41
3.1 Chapter introduction ...... 41
3.2 Exploratory research design ...... 41
3.3 Participant sample selection and interview format ...... 43
3.4 Structure of the interview format ...... 45
3.5 Research objectives ...... 45
3.6 Audio transcription and data analysis technique ...... 46
3.7 Exploratory study results ...... 46
3.7.1 Research results related to uncovering the effect that collaborative communication theory has on relationship quality ...... 47
3.8 Exploratory research findings and relevance to literature ...... 53
3.8.1 Research results on communication modality and relevance to literature and hypothesis development ...... 53
3.8.2 Research results on communication directionality and relevance to literature and hypothesis development ...... 53
3.8.3 Research results on non-coercive communication attempts and relevance to literature and hypothesis development ...... 54
3.8.4 Research results on communication formality and relevance to literature and hypothesis development ...... 55
3.8.5 Research results on power asymmetry and relevance to literature and hypothesis development ...... 55
3.8.6 Relationship quality and relevance to research results ...... 56
3.9 Exploratory study research objectives overview ...... 56
3.10 Limitations of the exploratory study ...... 57
3.11 Hypothesised model ...... 57 viii
3.12 Alternative model ...... 59
3.13 Chapter conclusion ...... 62
Chapter 4: Descriptive and Causal Research Methodology ...... 63
4.1 Chapter outline ...... 63
4.2 Quantitative research methodology design ...... 63
4.3 Data collection method ...... 64
4.3.1 Quantitative study sampling procedure and sample size ...... 65
4.3.2 Administration of survey instrument ...... 67
4.3.3 Questionnaire design ...... 69
4.3.4 Modification of questionnaire to online format ...... 70
4.3.5 Protection of questionnaire information against online fraud ...... 72
4.3.6 Section 2: Scale items relating to research hypotheses ...... 73
4.4 Data preparation and data analysis techniques ...... 78
4.4.1 Univariate Analysis ...... 79
4.4.2 Multivariate Analysis ...... 79
4.5 Chapter summary ...... 82
Chapter 5: Descriptive statistics of respondents and trading relationships ...... 83
5.1 Chapter outline ...... 83
5.2 Section 1: Descriptive statistics of grower/winery relations...... 84
5.2.1 Duration of relationship with winery ...... 84
5.2.2 Volume of grapes supplied to winery ...... 84
5.2.3 Value of grapes supplied to winery by respondents ...... 85
5.2.4 Average price per tonne of grape supplied to winery ...... 86
5.2.5 Other wineries supplied and the amount of grapes supplied to those wineries...... 87
5.2.6 Business details of the winery that was supplied grapes ...... 88
5.2.7 Summary of trading relations of grape grower respondents ...... 92
5.3 Section 3: Descriptive statistics of respondents ...... 92
5.3.1 Size of the respondents‟ vineyards ...... 93 ix
5.3.2 Number of years respondents operating their viticultural business ...... 93
5.3.3 Number of people employed by respondents‟ businesses ...... 94
5.3.4 Wine region location of respondents‟ businesses ...... 95
5.3.5 Technical viticultural qualifications of respondents ...... 97
5.3.6 Summary of descriptive statistics of respondents ...... 98
5.4 Chapter Summary ...... 98
Chapter 6: An integrated model of buyer-seller relationships in the Australia wine industry ...... 99
6.1 Chapter outline ...... 99
6.2 Measurement model of constructs ...... 99
6.2.1 Evaluation of the outer model ...... 100
6.2.2 Evaluation of the inner model ...... 105
6.2.3 Results of the structural model ...... 110
6.3 Consideration of structural model results ...... 112
6.4 Alternative structural model estimation ...... 115
6.5 Power, Satisfaction and Trust cluster analysis ...... 124
6.5.1 Cluster analysis methodology ...... 125
6.5.2 Cluster 1: “Unsustainable Relationship” ...... 130
6.5.3 Cluster 2: “OK relationship” ...... 130
6.5.4 Cluster 3: “Good Relationship” ...... 130
6.6 Chapter conclusion ...... 132
Chapter 7: Discussion, conclusion and implications for further research ...... 133
7.1 Chapter outline ...... 133
7.2 Summary of the research process ...... 133
7.3 Hypothesis discussion ...... 135
7.3.1 H1: Direct modes of communication positively influence trust...... 135
7.3.2 H2: Direct modes of communication positively influence satisfaction ... 135
7.3.2.1 H1a: Direct modes of communication positively influence relationship quality...... 136
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7.3.3 H3: Indirect modes of communication negatively influence trust ...... 136
7.3.4 H4: Indirect modes of communication negatively influence satisfaction. 136
7.3.4.1 H2a: Indirect modes of communication negatively influence relationship quality...... 137
7.3.5 H5- Uni-directional communication from the winery positively influences trust ...... 137
7.3.6 H6- Uni-directional communication from the winery positively influences satisfaction...... 138
7.3.6.1 H3a- Uni-directional communication from the winery positively influences relationship quality...... 138
7.3.7 H7- Non-coercive communication attempts from the winery negatively influence trust...... 138
7.3.8 H8- Non-coercive communication attempts from the winery negatively influence satisfaction ...... 139
7.3.8.1 H4a- Non-coercive communication attempts from the winery negatively influence relationship quality...... 139
7.3.9 H9- Formality of communication from the winery negatively influences trust ...... 139
7.3.10 H10- Formality of communication from the winery negatively influences satisfaction...... 140
7.3.10.1 H5a- Formality of communication from the winery negatively influences relationship quality...... 140
7.3.11 H11- Power asymmetry in the relationship, favouring the winery, is decreasing growers trust in the winery...... 141
7.3.12 H12- Power asymmetry in the relationship, favouring the winery, is decreasing growers‟ satisfaction with the winery...... 141
7.3.12.1 H6a- Power asymmetry in the relationship, favouring the winery is decreasing grape growers perceptions of relationship quality...... 141
7.4 Cluster analysis results discussion ...... 142
7.4.1 “Unsustainable Relationship” cluster ...... 142
7.4.2 “OK relationship” cluster ...... 143
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7.4.3 “Good Relationship” cluster ...... 144
7.4.4 Questionnaire item results discussion, by cluster ...... 144
7.4.5 Cluster results summary ...... 146
7.5 Research Question Summary ...... 146
7.5.1 Question 1: Which relational constructs constitute relationship quality? . 147
7.5.2 Question 2: Which elements of the grape grower/ winemaker relationship affect grape growers‟ perceptions of relationship quality? ...... 147
7.5.3 Question 3: Are there any commonalities between wine grape growers in their perceptions of relationship quality? ...... 148
7.6 Conclusion ...... 149
7.7 Study Limitations ...... 150
7.8 Recommendations for further research ...... 152
7.9 Study contribution ...... 153
7.10 Study implications for the Australian wine industry ...... 155
Appendix 1: Questionnaire ...... 156
Appendix 2: Cluster Analysis Results ...... 165
Appendix 3: IDI discussion questions ...... 175
Bibliography ...... 176
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Table of Tables Table 2.1: List of relational norms ...... 29 Table 3.1: Location and size of grape grower participants‟ businesses ...... 43 Table 3.2: Frequency of topic (code) discussion in in-depth interviews ...... 47 Table 4.1: Grape grower associations and private organisations that provided access to respondents ...... 68 Table 4.2: Questionnaire scale times regarding the formality of communication ...... 75 Table 4.3: Questionnaire scale items regarding winery feedback ...... 76 Table 4.4: Questionnaire scale items: non-coercive communication attempts ...... 76 Table 4.5: Questionnaire scale items regarding trust ...... 77 Table 4.6: Questionnaire scale items regarding satisfaction ...... 77 Table 4.7: Questionnaire scale items regarding power ...... 78 Table 4.8: Statistical criteria for model estimation via PLS ...... 82 Table 5.1: Years of contractual relationships between respondents and wineries ...... 84 Table: 5.2: Volume of grapes supplied to winery by grape grower respondents ...... 85 Table 5.3: Value of grapes supplied to winery by respondents ...... 86 Table 5.4: Price per tonne of grapes supplied to the winery by respondents ...... 87 Table 5.5: Number of other wineries to which respondents supplied grapes ...... 88 Table 5.6: Percentage of grape production supplied to the other wineries ...... 88 Table 5.7: Ownership of the winery to which respondents supplied grapes ...... 89 Table 5.8: Size of the winery to which respondents supplied grapes ...... 90 Table 5.9 Wine region winery was located in ...... 90 Table 5.10: State wineries were located in ...... 91 Table 5.11: Summary of the trading relationship of respondents and wineries ...... 92 Table 5.12: Size of respondents vineyards in acres ...... 93 Table 5.13: Number of years respondents operation of business ...... 94 Table 5.14: Number of people employed by respondents‟ businesses ...... 94 Table 5.15: Wine region location of respondents viticultural businesses ...... 95 Table 5.16: State respondents were located in ...... 97 Table 5.17: Viticultural qualification of respondents ...... 97 Table 5.18: Summary of descriptive statistics of respondents ...... 98 Table 6.1: Outer model evaluation of collaborative communication dimensions, trust, satisfaction and power...... 101 Table 6.2: Loadings and cross loadings of indicators and constructs ...... 106 Table 6.3: Correlations of the latent variables and the AVE square roots ...... 109 xiii
Table 6.4: Results of the structural model ...... 111 Table 6.4: Outer model evaluation of collaborative communication dimensions, trust, satisfaction and power of alternative model...... 116 Table 6.5: Loadings and cross loadings of indicators and constructs in the alternative model ...... 119 Table 6.6: Correlations of the latent variables and the AVE square roots ...... 122 Table 6.7: Results of the structural model for the alternative model ...... 123 Table 6.8: Factor analysis and results of Trust, Satisfaction and Power dimensions . 125 Table 6.9: Questionnaire item mean, median and standard deviation score by cluster ...... 127 Table 6.10 Summary of cluster analysis results ...... 131
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Table of Figures Figure 3.1: Conceptual model of grape grower perceptions of relationship quality in the Australian wine industry ...... 58 Figure 3.2 Alternative model based on uni-dimensional definition of relationship quality and grape grower perception of collaborative communication and power asymmetry ...... 61 Figure 4.1: Questionnaire scale items regarding the mode of communication ...... 73 Figure 6.1 Conceptual model of grape grower perceptions of relationship quality in the Australian wine industry ...... 110 Figure 6.2 A graphical representation of the of main structural equation model results ...... 112 Figure 6.3 Alternative model based on uni-dimensional estimation of relationship quality ...... 115 Figure 6.4 Graphical representation of the alternative structural model results ...... 124
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Chapter 1: Introduction
1.1 Chapter outline In this chapter the Australian wine industry, in particular the current state of grape grower and winery relationships is discussed. The objectives of this study, including the design of the research and research problems, are presented and a justification for using the Australian wine industry as a context to test the research problems and objectives is discussed. The chapter concludes with a summary of the composition of the thesis.
1.2 History of the Australian wine industry Wine in Australia has existed since European settlement of the country. Grape vines were brought to Australia from Brazil by Captain Arthur Philip in the late 1700s and the vines were planted around what is now Sydney and flourished there (Wine Australia, 2009). Grapes were then planted in areas such as New South Wales, Tasmania and Victoria with mixed success; production mainly satisfied export demand, generally from England. The discovery of gold in eastern Australia in the mid-1800s dramatically increased the consumption of wine and, as a result, vines were planted widely (Culture Portal, 2009).
The time period from the early 20th to mid-20th century saw two world wars, and the resettlement of soldiers from those conflicts contributed to the rapid increase of wine consumption, mainly driven by the consumption of fortified wines. The consumption of fortified wines was derived from a cultural link with the United Kingdom. However, by the 1960s and 1970s an influx of European migrants resulted in changing consumption patterns. Table wine styles (for example red, white and sparkling wines) began to be consumed and this was also aided by a more cosmopolitan view of life by Anglo- Australians (Walsh, 1979). Young Anglo-Australians started to travel to European countries and this spawned an appreciation of Mediterranean cuisine and associated wine consumption patterns.
The Australian wine industry became hampered by an oversupply of grapes in the mid- 1980s, and 2500 acres of vines were removed; however, an export led boom in demand 1 for Australian wine (led by the UK and USA markets) in the late 1990s saw an undersupply of grapes and consequently such removals in the 1980s were regretted (Clancy pers comm. April 2009). A boom in production and export sales in the early 21st century created great wealth and prosperity for the industry, mainly led by favourable taste preference of consumers in export markets and favourable exchange rates (Stanford, 2007).
The preceding discussion has shown that the wine industry has gone through periods of economic prosperity, specifically five periods (Osmond & Anderson, 1998). These “booms” in economic prosperity are summarised chronologically as follows:
the first boom in the mid-1850s due to discovery of gold in Victoria and New South Wales and aided by a trebling of the Australian population; the second boom in the late 1880s due to domestic increases in consumption and export growth, particularly to the British market; the third boom in the mid-1920s led by the export of fortified wine to the United Kingdom and aided by land development subsidies for grape production granted by the federal government; the fourth boom in the 1960s attributed to changing domestic consumer tastes from fortified wine consumption to table wine consumption aided by a more cosmopolitan view on life which resulted from Australians travelling overseas and the migration of European migrants; and the fifth boom in the late 1980s due to strong export demand from Europe and North America; the North American consumption of Australian wine was aided by favourable exchange rates, successful branding strategies and a focus on the consumption of wine for health reasons. (Osmond & Anderson, 1998)
1.3 Current state of the Australian wine industry The Australian wine industry has expanded markedly throughout the 20th century in terms of the area under vine and the production of grapes. Winetitles (2010) states that in 2009 the total area under vine was 162,550 hectares with a grape crush of 1.71 million tonnes. This is a decrease of approximately 7% from the 2008 vintage. Winetitles (2010) lists 2420 companies that sell wine commercially, of which two companies, Foster‟s Group and Constellation Wine Australia, account for
2 approximately 45% of all branded wine sales with the top 20 companies accounting for 90% of total sales. These figures indicate that the remaining 2400 producers compete for 10% of the total sales of branded, bottled wine.
Evidently the Australian wine industry‟s sales have consolidated, with the largest wine producers dominating sales. The increase in wine production volume has coincided with a less than equal increase in sales, with a current wine inventory level of 2.1 billion litres in 2006. The current stock to sales ratio of approximately 2:1 is unfavourable. With a current stock inventory of 1.9 billion litres and estimates stating that a ratio of 1.7:1 is required (AWBC, 2007; ABS, 2009a), the Australian wine industry is producing an excessive amount of grapes and an oversupply exists.
Approximately 60% of the wine produced in Australia is exported and consequently export markets are of critical importance to the industry‟s well-being (Wine Australia, 2009). However, as previously mentioned, the effect of decreasing wine export volume is compounded by the decreasing value per litre of exported wine and, therefore, has resulted in a lower financial return for Australian wine producers. As such, in the year to December 2009 the value per litre of exported wine decreased by 15% (Winetitles, 2010). Therefore wineries have experienced decreasing earnings, with the majority of Australian wineries (under $20 million in revenue) receiving losses before tax in the year to 2009 (Deloitte, 2009).
Such financial pressures experienced by the wineries are being passed onto grape growers, who are in turn experiencing financial hardship. Part of the industry‟s hardship has also been attributed to issues related to climate change. Frost, and particularly drought, have caused a reduction in yields resulting in less income for the grape grower; however, the lack of water has required grape growers to purchase water at ever increasing prices, which has placed them under further cost pressures (Hayman et al., 2007; Stone, pers comm., February 2010).
There have also been other issues relating to cost pressures affecting the 4500- 6500 grape growers in Australia and much of this is attributed to growers receiving lower prices for their grapes (ABS, 2009b; McKenzie, pers comm., May 2009). While statistics show that grape prices increased in the 2007 vintage (up to a 40% increase in warm climate areas) with the reduced yield (due to frost and drought) increasing prices, when viewed historically there has been an average decrease in price of 50% from the 2001 vintage (ABARE, 2009; McKenzie, pers comm., May 2009). This price reduction
3 is in contrast to the past; grape prices increased by 73% from 1987 to 1997 (Osmond & Anderson, 1998).
Grape growers are currently experiencing poverty and this can be viewed against a history which shows that grape growers have received lower prices for their grapes in the past, particularly in the mid-1980s where a glut of grapes resulted in markedly lower prices and the destruction of vines (IAC, 1995; Clancy pers comm., April 2009).
The current oversupply of grapes is also affecting wineries; to alleviate financial pressures, some wineries have been cancelling, and not renewing, grape supply contracts. As a result of the actions of certain wineries during this period, many relationships between them and grape growers have become adversarial and have resulted in inefficiencies which may harm the Australian wine industry (Speedy, 2006).
The adversarial nature of grape grower and winery relationship is not confined to the Australian wine industry, nor to current times. In 1910-1911, riots occurred in Champagne, France, due to grape growers‟ perceptions that the prices they were receiving for their grapes were unfairly low (Phillips, 2000). The cause of the low prices was attributed to a power asymmetry wielded by the Champagne houses, as a result of there being a small number of houses and a large number of growers in the region. This is also evident in current times where a power asymmetry favouring Champagne houses is resulting in lower grape prices for their grape growers (Charters & Menival, 2010). Furthermore, in recent times, particularly in Europe, there has been conflict involving grape growers, wineries and retailers. For example, grape growers in the south west of France have highjacked trucks, vandalised wine retail outlets, and destroyed wine as they perceived that the low prices they received for their grapes was a result of power wielded by wineries and the importation of cheap wine by wine retailers (IAC, 1995; Quinn, 2008). The conflict is also evident in other European countries such as Hungary and Kosovo where local grape growers, unable to find buyers for their grapes, protested and took violent action against their respective governments in order to gain better price terms (Farmers protest in Kosovo town turns violent, 2010).
Therefore, the relationships between grape growers and wineries, not only in Australia, have resulted in conflicts and potential inefficiencies. In Australia, the inefficiencies and their effects could be compounded by strategic changes to wine industry policy by the peak industry bodies. The industry is attempting to reposition itself to focus on the
4 production of quality wines (as opposed to volume production) and emphasising regional branding (Hobley & Batt, 2005; Deloitte & WFA, 2006) hoping that a focus on quality production will allow the wine industry to gain a strategic competitive advantage (Chong, 2007).
Collaboration and long term relationships are crucial to the development of wine products which meet appropriate quality specifications (CIE, 2004). Quality parameters, while set by the purchasing winery early in the growing season, are controlled by the grower with such elements as pH level, pest and disease control, grape sugar content and berry size contributing most to wine quality (Spawton & Walters, 2003; Clancy, 2005). To obtain grapes of a certain quality parameter, the winery must engage in relational activities that engender a higher level of relational quality for the grape grower. Higher levels of relationship quality provide greater loyalty from the grape grower to the winery and have the added effect of continued financial returns for the grower. In light of the oversupply of grape and wine affecting the industry, and the resultant lower grape price returns for grape growers, it is of interest to observe the grape growers‟ perceptions of relationship quality.
Numerous wine industry and government publications have highlighted the need for better relationships between grape grower and wineries. For example, the former Industry Assistance Commission (now referred to as the Productivity Commission) in a report to the federal government advocated improved relationships and better supply chain coordination between grape growers and wineries to increase grape quality and higher levels of trust between the two actors (IAC, 1995). Spawton & Walters (2003) claim that better coordination of grape growers is required and that elements of these relationships, such as communication, need to be improved. Chong (2007) advocates that relationships between the two partners need to be developed further, particularly in communication between the actors, and this notion is affirmed by Brown (2008) who further comments that good communication is needed to maintain and enhance relationships between the two.
1.4 Research problem and objectives and thesis title The rationale behind the research problem for this study was to conceptualise and measure the relationship quality and its effect on other relational variables from a wine grape seller‟s perspective in the Australian wine industry. In doing so, an integrated
5 model of the buyer-seller relationship in the Australian wine industry was created and this notion is reflected in the title of this thesis.
Three research questions were devised for this study:
1. which relational constructs constitute relationship quality? 2. which elements of the grape grower/ winemaker relationship affect grape growers‟ perception of relationship quality? 3. are there any commonalities among wine grape growers in their perceptions of relationship quality?
Quality in a wine product is based on the quality of the grapes produced, with approximately 60% of the work required to make a high quality wine derived from the grapes (Scales, Croser and Freebairn, 1995). In order to obtain the grapes of a desired quality, the winery must liaise with a grower during the growing season (from approximately August to April in the Southern Hemisphere) and therefore much emphasis is placed on the grower-derived inputs. Thus, it is of interest for the winery to liaise appropriately with the grower.
This notion of grower-derived wine quality is of particular importance to the Australian wine industry due to changes in the marketing and promotion of Australian wine to emphasise quality and regionality (Henry, 2009). As a consequence, the suppliers of wine grapes in this industry are becoming increasingly important in the supply chain, and their needs and wants must be uncovered and satisfied. This study has attempted to achieve this.
From an economic perspective, the wine industry is of great importance to the Australian economy, further justifying its selection as a research subject. The wine industry accounted for approximately $2.6 billion of domestic and export sales in 2009 (Winetitles, 2010). The number of wineries in Australia has also increased by approximately 4.3% from 2008 to 2009, with the number of wineries having more than doubled since 2000 (Winetitles, 2010). The wine industry directly employs 28,000 people and indirectly employs others in areas such as hospitality, retail and wholesaling (DFAT, 2009). Currently there is no solid information available regarding the increase or decrease in the number of grape growers; however, approximately 4500 to 6500 growers exist in the industry (ABS, 2009b; McKenzie pers comm., May 2009). Further highlighting the industry‟s economic importance is the fact that it has a production presence in all states and territories in Australia except for the Northern Territory 6
(Winetitles, 2010) and the industry has production entities (wineries and grape growers) that are small, medium and large in size, both publicly and privately owned (Winetitles, 2010). It is evident that the Australian wine industry is of vital importance to the Australian economy, particularly to its rural sector, and is therefore a significant area of research.
Recent times have seen an upheaval in the Australian wine industry. Apart from the issues previously discussed, grape growers have experienced decreasing grape prices and as their future importance in the wine industry supply chain is being cemented by marketing initiatives emphasising grower-derived inputs (e.g. quality and regionality), it is of interest to investigate their perceptions of the relationship between the two actors; this was an objective of this study (ABARE, 2009; Henry, 2009).
Furthermore, the marketing initiatives place greater importance on the grower in the supply chain and, therefore, examining the relationship that wine producers have with growers will allow wineries to tailor their grower liaison efforts to best satisfy grower needs. The quality of the relationship which growers have with wineries is of importance to wineries as the increasing importance of growers in the supply chain will shift the emphasis to satisfying grower needs. As a result, the wine industry provides a fertile area of research in any attempt to uncover supplier related perceptions of relationship quality.
1.5 Research Design and significance of the study From an ontological perspective, the study involved interviewing and surveying Australian wine grape growers about their perceptions of communication and power asymmetry in the relationship they have with wineries. The study was designed employing a two-step process, often referred to as a multi-method or mixed method approach, whereby qualitative and quantitative methods were integrated into the study (Carson & Coviello, 1996). From an epistemological perspective, the study utilised a scientific, validity approach which was used to develop and test hypotheses in the quantitative phase of the study (Wacquant, 1992; Cohen & Maldonado, 2007).
However, the qualitative phase of the study employed an interpretive, constructivist perspective as this phase of the study explored concepts of relationships and required interpretation by the researcher (Gall et al., 2003). The literature discusses three types of research, namely exploratory, descriptive and causal (Kinnear et al. 1993). This study 7 contained these three types of research; this approach is common in agribusiness PhD studies (see Storer, 2005; Hobley, 2007).
Firstly, an exploratory phase was deemed important as it allowed for the development of a clearer understanding of the phenomena to be studied (Zikmund, 2003). This initial stage of the research was deemed appropriate as the relationship between grape growers and wineries, particularly related to the elements of communication and relationship quality, had not been extensively investigated in the past. As these factors are complex, an exploration was vital in order to gain an insight into their interactions (Zikmund, 2003). The exploratory research stage utilised qualitative research methods, namely in- depth interviews (Ticehurst & Veal, 1999).
Descriptive research was also used in order to gain an understanding of the phenomena such as frequencies and means, particularly the descriptive statistics of the respondents and their trading relationships with wineries (see Chapter 5). The descriptive research phase allowed for the validation of the sample against the sample frame, and the data was captured via the use of a questionnaire.
While descriptive research has the purpose of describing phenomena and predicting linkages between variables, explanatory, causal research was required to verify assumptions that were made in the exploratory phases, such as the hypotheses that were formulated, and was performed using structural equation modelling (SEM) utilising partial least squares regression. The purpose of using SEM was that is has the ability to test entire models (i.e. the conceptual models devised in the exploratory phase) (Baumgartner and Homburg, 1996; Steenkamp & Baumgartner, 2000). The model tested in the causal stage of the research involved various constructs (i.e. collaborative communication element, power and relationship quality) which were operationalised in a questionnaire using multiple questionnaire items derived from previous studies (Hair et al, 2006).
The causal stage of the research process was used based on the understanding that empirical research is required to understand and to extend business to business (B2B) marketing theory (Medlin, 2001; Donaldson & O‟Toole, 2000; Plewa, 2005).
Furthermore, a large number of studies that utilise the grape grower and winery relationship context, or the wine industry as a unit of analysis, are qualitative or exploratory in nature rather than empirical or mixed method (qualitative and quantitative combined) studies (see Hall, 2004; Benson-Rea, 2005; Rampersad, 2008). 8
After completion of the causal stage of the study, an exploratory phase was again employed (namely cluster analysis) to uncover the nature of relationships between grape growers and wineries and to categorise the relationships based on relationship dimensions (Everitt, 1996; Janssens et al, 2008).
In summary, the study contained both a constructivist and positivistic epistemological approach due to the three research methods employed: exploratory, descriptive and causal. Firstly, an exploratory, qualitative phase allowed for a conceptual understanding of the constructs investigated, and the production of a conceptual model and was constructivist in nature as it was based on viewing and interpreting the grape growers‟ perspectives but not trying to measure them (Guba & Lincoln, 2005). The second phase of the study was descriptive and employed quantitative methods whereby descriptive statistics were obtained, mainly to validate the sample. The third phase of the study was quantitatively causal whereby the conceptual model developed in the exploratory phase was tested. Finally, an exploratory quantitative method was employed, via the use of cluster analysis to uncover the nature of the relationships between grape growers and wineries. As such, the final three stages of the research employed a positivistic, epistemological paradigm due to the scientific nature of the data analysis that employed the testing of hypotheses and the categorisation of data based on clusters (Babbie, 2004).
To develop instruments of measurement, such as the questionnaire, wine industry experts, such as peak body leaders, viticultural consultants, winemakers and wine industry commentators, helped in their development and validation. This was particularly the case in the development of the questionnaire used in the descriptive and causal stages of the study.
This study differs from previous studies that explored a similar context (wine industry) as it uses a mixed-method approach, unlike studies that are qualitative in nature (see Benson- Rea, 2005; Rampersad, 2008). This study employs a similar method and context as that used by Hobley (2007) in that the relationship between grape growers and wineries is explored from a B2B and a relationship marketing perspective; however, this study extends Hobley‟s (2007) work by focussing on a particular element of that study, namely communication elements as proposed by Mohr & Nevin (1990) and Mohr et al. (1996) in their theory of collaborative communication. Furthermore, this study is different from other studies that have investigated communication elements between agribusiness buyers and suppliers (of which grape grower and winery 9 relationships are examples); for example, in Mohr & Nevin (1990) and Mohr et al, (1996), collaborative communication elements are empirically tested as opposed to using an inter-organisational information management system (IOIMS) which differs in its perspective of communication.
1.6 Structure of the thesis This thesis is structured as follows:
Chapter 2 discusses the theory relating to buyer-seller relationships and business to business interaction, particularly related to the dimensionality of relationship quality and the relational norms that affect relationship quality.
Chapter 3 outlines the methodology of the data collection in the exploratory stage of the study and presents its results. The chapter also presents the conceptual models that are tested by later stages of the study.
Chapter 4 discusses the methods used in the descriptive and causal stages of the study such as uni-variate (descriptive statistics) and multivariate statistical methods (structural equation model utilising partial least squares regression).
Chapter 5 outlines the quantitative results of the descriptive stage of the study, mainly concerning the trading relationships and business details of the respondents of the study.
Chapter 6 discusses the results of the causal stage of the study, and presents the results related to the conceptual models. It also identifies commonalities between the grape growers in terms of relationship quality via cluster analysis.
Chapter 7 summarises the main findings of the study and provides a conclusion and areas for further research.
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Chapter 2: Literature Review
2.1 Introduction This chapter outlines the academic literature regarding the research problems and objectives detailed in Chapter 1. The chapter commences with a brief summary of Chapter 1, followed by a discussion of the literature regarding business to business interactions, relational norms and relationship quality. The chapter concludes with a summary of the discussion and a section introducing the following chapter.
2.2 Australian wine industry context for discussion of literature The Australian wine industry is currently undergoing a period of economic hardship. Due to issues such as production oversupply, maturing markets, unfavourable exchange rates in export markets and international retail consolidation, many wineries are experiencing economic losses (Henry, 2009; Deloitte, 2009). The financial losses experienced by the wineries are being passed onto grape growers through the lowering of grape prices and the cancelling of contracts (Hobley & Batt, 2005; ABARE, 2009). However, the wine industry is establishing a marketing strategy designed to mitigate the negative economic effects which aims to bring prosperity to the industry. The strategy aims to produce and promote quality wine and regionality in wine products. Both of these dimensions are grape grower derived; therefore, the inefficient relationships that exist will need to be rectified, and information regarding the grape grower perspective of the relationship will require investigation. As grape growers will need to be engaged in relationships in order to accomplish the strategic marketing objectives, information will have to be obtained with respect to the grape growers‟ perception of the relational dimensions such as relationship quality.
As growers have received lower prices for their produce (grapes) in these harsh economic times, it is of interest to observe how grape prices affect relationship quality. The issue of improving relationships between grape growers has been highlighted in
11 academic and wine industry trade literature, particularly in relation to elements of the relationships, such as communication, between the two actors (IAC, 1995; Spawton & Walters (2003; Chong 2007; Brown 2008)
Firstly, let us consider of the generic context of the research, namely business to business interactions.
2.3 Business to business interaction The focus of this study is the interaction between grape growers and wineries and as such, the general context of this study is business to business (B2B) interaction. There are aspects of the interaction which can be discussed and the differences between B2B and business to consumer (B2C) interactions which can be observed. The comparison between the two is important as it gives a perspective between the two fields of study in marketing. The main areas of the B2B interaction that will be discussed in this section of the chapter are B2B purchasing, and relationship marketing in B2B markets. Firstly, the differences between consumer (B2C) and industrial (B2B) markets will be discussed.
2.3.1 Industrial markets and inter-firm relational development Purchasing occurs in both business to business (B2B) (often called industrial markets) and business to consumer markets (B2C) (often referred to as consumer markets). However, there are many differences between the two. For example, in B2B markets, organisations acquire goods and services that are resold to other industrial markets (such as private businesses, governments or institutional markets such as schools and hospitals) and in B2C markets the goods are sold for personal consumption by consumers (Kotler et al., 2010). However, B2B and B2C markets do not work in isolation. B2B markets create products that are ultimately used in B2C markets, with the wine industry providing a clear example. Wine grapes, a B2B product as grapes are made by a business (grape growers) and sold to a business (a winery), are transformed into wine which is then sold in B2C markets to consumers. The demand by the consumer will shape the overall nature of the product with firms striving to produce products that are demanded by consumers (Hutt & Speh, 2010). The consumer demand characteristic will be observed by the B2B actors, and therefore the nature of the
12 product produced in the B2B phase will be modified to meet the needs of the end consumer.
While the purchasing decision process has been briefly discussed in this section, the next section will involve a greater discussion of industrial (B2B) purchasing and‟ in the first instance, interfirm relationship development.
Actors in B2B interaction develop relationships, and these relationships develop over time; the development has been shown to occur in various phases. Wilson (1995) discusses a relationship development framework similar to Dwyer et al. (1987). In the first phase, “partner selection”, Wilson (1995) posits a more active firm pair than that of the “awareness” phase of Dwyer et al. (1987), whereby the actors are already conducting business with each other and a deeper relationship is sought by one or both actors (Morris, 2005). The second phase, “defining purpose”, involves creating a set of activities that are expected by each partner and is characterised by a higher level of communication. The third phase, “setting relationship boundaries”, evolves by a process that may not possess a legal or explicit nature. The fourth phase, “creating relationship value”, involves obtaining benefits from the partnership that would have been unattainable by each firm independently. It is in this phase that “relationship- specific investments” assume a prominent role, with these assets being similar to Thibaut & Kelley‟s (1953) relational norm theory in that cooperation and commitment are both active in this phase. In the final phase, “relationship maintenance”, relational elements such as trust and satisfaction become fixed and are omnipresent in the relationship.
Therefore, in regard to B2B relationship development, incorporating social exchange theory, there is a development phase where boundaries and duties are set and if the expectations are met, the relationship grows (Thibaut & Kelley, 1953). As the relationship develops further and commitment becomes greater between the two actors, relational norms (such as trust and satisfaction) are engendered. Overall, the discussion of relational development has one common element: the development of the relationship requires that both members consider the exchange worthwhile for commitment to the relationship to occur.
While B2B interaction, such as relational development, purchasing and relationship marketing, have been discussed, a further investigation into B2B marketing, the context of this study, is required and is the focus of the next section of the chapter.
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2.4 Business to Business Marketing The focus of study into business to business (B2B) marketing has shifted over time. Much of this change is due to the dynamic nature of firms and the fact that firms are increasingly understanding the importance of buyer supplier management, as there is an understanding that in order to create products and services to sell to buyers, firms must manage their inter-firm relationships (Ulaga, 2001). This area of marketing has seen a shift from a focusing on the exchange between firms, to an emphasis on relationships and a focus on inter-firm networks. The discussion in this section of the chapter will focus on these three areas. However, the main function of B2B marketing is the purchasing of goods and as such the next section will discuss this concept.
2.4.1 B2B purchasing As briefly discussed earlier, B2B purchasing of products differs greatly from B2C purchasing. As this study is focused on B2B interactions, a more detailed discussion of B2B purchasing will be undertaken.
The literature discusses industrial purchasing from numerous viewpoints. The main perspective includes those of a function (Barnhill & Lawson, 1980; Anderson et al., 1994; Trent & Monczka, 1998; van Weele, 2000), as a process (Robinson et al., 1967; Ozanne & Churchill, 1971; Webster & Wind, 1972; Kelly, 1974; Bradley, 1977; Barnhill & Lawson, 1980), and as a supply or value chain (OK Porter, 1985; Hines, 1993; Hines et.al, 2000; van Weele, 1994).
The role of purchasing as a function in a B2B context is to procure supplies (Lysons & Gillingham, 2003). The term “function” is derived from the notion that many functions within a business are coordinated to purchase a product. In relation to this, Barnhill & Lawson (1980) discuss the operations function in purchasing supplies for a business as revolving around the coordination of activities within a business towards purchasing, and if this is done satisfactorily, then the business will excel during the exchange of products. Barnhill & Lawson (1980) stress that the exchange is complex and involves activities such as production, finance, distribution and promotion, and that each of these activities is the responsibility of a separate division within a business that must coordinate with the other elements in order for the purchasing function to be successful and at lowest cost. Also, in relation to purchasing as a function, Leenders & Fearne 14
(1997) and Duffy (1999) discuss purchasing as involving various elements such as the flow of materials and supplies, the organisation of inventory, the development of supplier relationships, and the notion that the purchasing function should strive to achieve the maximum gain at the lowest cost, which in turn gains the business a competitive advantage. This concept is highlighted by Trent & Monczka (1998) who discuss the procuring of resources for a business as involving functional groups within the business that work to acquire products, and to strive to reduce transaction costs, improve product quality, reduce lead times and use better technology in order to ultimately gain greater customer satisfaction. The concept of purchasing as a process is highlighted by Anderson et al. (1994) who comment that not only do firms strive to maintain excellence in the functions involved in purchasing within the company, such as the activities highlighted by Barnhill & Lawson (1980); they also comment that purchasing also involves various networks outside of the business. Two firms purchasing in a dyadic relationship are not only connected to each other via the purchasing of goods, but also by the relationship with secondary, ancillary suppliers who work with both the buyer and supplier to aid the purchasing process. This concept is also discussed by Trent & Monczka (1998) who comment that purchasing is increasingly becoming network oriented with suppliers, buyers and third party providers linking together increasingly through electronic means to purchase goods. Trent & Monczka (1998) stress that due to the complex nature of modern purchasing, involving various actors, in order to improve the function of purchasing the purchasing manager needs to continually monitor and appraise the various actors to improve the functions and therefore, gain a competitive advantage.
The previous discussion has alluded to the fact that the role of purchasing as a process within a firm is highly complex. This notion is further pointed out by Barnhill & Lawson (1980) who comment that purchasing acts like a process in that a two way action occurs where a flow of money and value is exchanged for a good, service or item of value. Other early works in this area further discuss the specific processes involved. For example, Ozanne & Churchill (1971) discuss the concept of the Industrial Adoption Process which leads to the purchase of industrial products. This process involves various elements such as:
(i) factors that activate the purchasing process, such as equipment capacities, obsolescence and labour shortages;
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(ii) Purchasing Directing factors which are factors that purchasing decisions are based on such as lead times quoted by suppliers, product attributes and past experiences; (iii) duration of the buying process, such as the length of time from problem awareness to purchase; (iv) alternative evaluations of supplier products and cost benefit analyses; and (v) the use of information to make decisions about which product to purchase.
The early works in industrial purchasing heavily focus on the specific processes involved, such as those commented on by Ozanne & Churchill (1971) shown above. Kelly (1974) further discusses the process, particularly the decision making process involved, and relates this closely to that which is performed in consumer decision- making behavioural processes (Schiffman et al. 2001). This process involves the recognition of a need, a search for alternatives, an alternative evaluation and a decision on a product; however, Kelly (1974) states that a difference occurs in that the approval process for purchasing is far more involved as various people in the buying centre are required to authorise the transaction as opposed to an individual making a decision (Rosenboom, 2004).
Webster & Wind (1972) comment further in relation to an organisation‟s decision making process in that the purchasing of goods and services is based around four elements: the environment in which the process is occurring, the abilities of the organisation in terms of its technology and management structure, the buying centre of the organization, including its structure and leadership style, and the individual participants in the decision making process. These elements combine to affect the decision making process, particularly the nature of the process including its duration and complexity. This process is more developed by Kelly (1974) who likened the process to consumer purchasing behaviour and did not highlight the specific differences that occur in industrial purchasing.
Bradley (1977) further developed the notion of industrial purchasing, stating that, as opposed to consumer purchasing, numerous people are involved in the process, and that the transaction involves issues such as delivery terms and after sales services such as technical support which may occur in consumer markets but is less of a concern. Bradley (1974) also mentions that the type of product purchased will influence the purchasing process such that a spectrum exists from routinely purchased products that require little alternative evaluation to buying centre considerations of a capital product, 16 such as plant equipment and buildings that require great scrutiny and effort in the decision-making and purchasing process. Bradley (1974) also discusses the purchasing process and echoes the works of Ozanne & Churchill (1971), Webster & Wind (1972) and Kelly (1974) when stating that when a purchasing need is felt by the company, a shortlist of suppliers and products is made, contracts are awarded and a product is purchased.
Much of the work focusing on purchasing as an industrial process is prescriptive in that it talks specifically about the individual processes involved. Later work focusing on industrial purchasing concentrates more on the functions involved. In summary, purchasing by firms is a strategic process involving various units of a company and decision making processes. These processes involve consideration as to the function and profitability that a product will offer and the notion that a relationship between the firms involved is complex and requires effort to establish and maintain.
The discussion has also highlighted the fact that industrial purchasing processes involve many people within a company, generally described as a buying centre or team. This team is highly complex and skilled in tasks required in the purchasing process, such as alternative evaluation, negotiation and the procurement of the product. It can be surmised that the abilities and talents of this team gains the company a strategic competitive advantage (Rosenboom, 2004). From a wine industry perspective, many of the firms, whether they be grape grower or winery, are small in size; many are considered SMEs (Winetitles, 2010) and as such, the decision making process may only be made by one person; for example, the owner of the business may make the decision. In this case, the grape grower business or winery owner may be the only decision maker and therefore the process of purchasing may differ in complexity from those discussed in the literature, which tend to involve large corporations.
The notion of purchasing involvement in a supply chain can be discussed from a value or supply chain perspective. In Porter (1985), the value chain perspective is discussed as having many activities such as human resources involvement, and technology and facilities supported by activities such as logistical functions (both outbound and inbound) that ultimately result in product acquisition and value gained by the customer. Effectively, Porter‟s (1985) premise is that material management (which includes purchasing of materials for manufacture reasons) adds value and that if managed appropriately will gain customer satisfaction. Hines (1993) adds to Porter‟s value chain system by discussing an Integrated Materials Value Pipeline which shows numerous 17 pipelines of activities that exist in a supplier‟s network that aid the procurement of product. Hines (1993, pg. 13) is clear in pointing out that the concept of value raised by Porter (1985), namely that the “...value built into a company‟s products is the result of activities required to design, produce, market, deliver and support that product” and that these activities are based on the human capabilities of the company. Hines (1993) adds that the problem with Porter‟s (1985) value chain model is that is focuses too much on a firm‟s profit and not enough on customer satisfaction, and that the Porter (1985) model does not fully show the interconnectedness of the firm‟s value chain, such as the interconnectedness of human resources functions, materials and engineering research development and marketing that are used to create values which Hines (1993) proposes in the Integrated Materials Pipeline. The premise is that these sections of the firm are driven by the needs of the consumer. Effectively Hines (1993) discusses the value chain perspective from the consumer and then “up” the chain, whereby the function of the firm, including the purchasing process, are fashioned to gain the maximum level of customer satisfaction. Therefore, Porter‟s (1985) and Hines‟ (1993) perspectives of B2B purchasing both put forward the notion that a “chain” or process, starting from design and raw product, and ending at the consumer, will involve some sort of purchasing and that this purchasing, between firms, is important to the ultimate success of the firms.
Furthermore, Porter‟s value chain model (Porter, 1985; Porter 1990) has been discussed and elaborated on in a wine industry context (Spawton & Walters, 2003). Spawton & Walters (2003) discuss wine as a valuable product and discuss the way in which the wine supply chain can be coordinated to create value which will give wine consumers satisfaction. The processes in the Porter value chain, adapted by Spawton & Walters (2003), include grape production facets such as the coordination of grape growing with wine making parameters such that grapes of a specific quality are obtained in order to create a wine that gives consumer value. Spawton & Walters (2003) note that relational norms such as communication between the two actors will aid in the creation of consumer value, which should be a basis for a sustainable competitive advantage of the Australian wine industry.
The purchasing literature, as discussed above, has concentrated on three perspectives of purchasing. Early literature discusses purchasing mainly from a process perspective that appears very logistical in nature. Later literature discusses the intricacies of the functions performed in purchasing, including the idea of customer satisfaction being an
18 important factors in purchasing, as proposed by value chain literature. The recent literature tends to discuss purchasing more from a network perspective, whereby individual firms have various networks of suppliers that aid and facilitate the purchasing of products. The preceding literature has shown this evolution of thought from process to function and then relationship networks.
2.4.2 Exchange relationships Early B2B marketing theory focuses heavily on the concept of relational exchanges whereby firms exchange products and people in order to be profitable and therefore to gain consumer value (Dwyer et al. 1987). Bagozzi (1975) adds that an exchange is a direct transfer of tangible entities between two parties. The basic premises that exchange relationships are important to the firm are that:
i) The exchange serves as a focal event between two or more parties that aid in product transfer; ii) The exchange allows for the individual firms to identify the roles they play in the exchange which allows them to recognise weaknesses in the roles and better them, thereby aiding the exchange; iii) The exchange allows for the product that is to be exchanged to be examined for faults or benefits of the product to be realised; and iv) The exchange can be observed so that the parties in the exchange can make judgements as to whether the exchange was successful or otherwise. (Dwyer et al. 1987)
While exchanges have numerous benefits to firms, as discussed above, they are mechanical in nature and have processes similar to industrial purchasing, discussed earlier in this chapter. This is shown by Frazier (1983) who highlights three processes in exchange relationships:
initiating processes whereby a product needing recognition is made and partner search (to fulfil at need) is initiated; an implementation process where the product flows between the two companies and therefore, an interaction between the firms occurs; and a review process whereby the exchange is evaluated in terms of the benefits of the product obtained and whether the goals were obtained.
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Bagozzi (1975) discusses the nature of exchanges and has categorised three types of exchanges:
i) A restricted exchange which contains two parties in a reciprocal relationship whereby A gives to B for example a buyer purchases a product from a supplier; ii) A generalised exchange which is considered to be an univocal, reciprocal relationship whereby there are at least three actors in the exchange but some do not benefit directly from the exchange. For example, a grape grower supplies grapes to a winery who then transforms it to wine and sells the wine to a retailer. The label on the wine bottle lists the grape growers details and as such the grape grower gains value and benefit due to consumer recognition (on the basis that consumers value this information); and iii) A complex relationship which is a mutual relationship between at least three parties with a direct relationship between each, such as a supplier- manufacturer-distributor relationship.
Bagozzi (1975) discusses the fact that within the exchange is a “medium”, some form of communication, which allows information to flow between each party. Furthermore, Bagozzi (1975) introduces the concept of social marketing which is a precursor to a discussion on relationships whereby relational norms occur through social interaction between the parties during the exchange, and these strengthen the relationship and aid in relational continuity. This concept of social marketing is similar to Thibaut & Kelley‟s (1953) relational norm concept imbedded within social exchange theory in that cooperation and commitment and other relational norms are imbedded in the exchange via social interaction.
Frazier (1983) also discusses a structure for inter-firm exchange. Frazier (1983) comments that the relationship has elements or “sub-processes” such as achieved influence, goal compatibility, role satisfaction, manifest conflict, conflict resolution and, finally, cooperation and effort, and these can be linked to the relational norm concept developed by Thibaut & Kelley (1953). The review process is an assessment of the benefits or losses achieved by each firm as a result of the exchange. Similar to the expansion phase in Dwyer et al.‟s (1987) theory is Frazier‟s (1983) model which shows the expansion phase as involving a great level of interaction between the two actors which results in continuing relations which create satisfaction for each partner. The concept of a structured, mechanical exchange is further developed by Weitz (1981) 20 who observed the exchange, not from a firm‟s perspective but from the personnel involved in the exchange, such as sales persons. Weitz (1981) discusses the personal characteristics of the sales person, such as demeanour and selling ability, which will affect the exchange; he also discusses the communicative abilities which aid the success of the exchange, in line with Bagozzi‟s (1975) social marketing concept. The rapport developed between the individuals involved in the exchange aid in the development of relational norms such as role satisfaction and conflict resolution which ultimately aid exchange success, similar to those proposed by Thibaut & Kelly (1953) and Frazier (1983).
Lambe et al. (2001) offers a comprehensive review of social exchange theory as applied to B2B relationship literature. They discuss the following four premises of social exchange theory:
1) exchanges result in economic and/or social outcomes;
2) the outcomes are evaluated over time to substitute exchanges to determine how much dependence is required on the exchange;
3) positive outcomes over time increase a firm‟s trust in their trading partner and commitment to that exchange; and
4) positive exchange interactions over time produce new relational exchange norms that govern the exchange relationship.
Blau (1964, 91) defines social exchange as “voluntary actions of individuals that are motivated by the returns they are expected to bring and typically do, in fact, bring from others.”, meaning that interactions are motivated by the notion that further benefits will occur to the actor if they keep interacting in a positive manner. The interactions are motivated by benefits such as common norms, roles, or goals and these elements act as incentives for the social interaction. A network of social relationships and group structures then begins to emerge. Finally, group norms and expectations become more solidified (Morris, 2005).
Blau (1964, p 92-93) distinguishes social from economic exchange by arguing that economic exchange entails specific obligations while social exchange “involves the principle that one person does another a favour, and while there is a general expectation of some future return, its exact nature is definitely not stipulated in advance”. As the future obligations are not specified, trust in the exchange partner is necessary for social 21 exchange. Such actions help to create a relationship that is long-term, as social bonds between the actors become strengthened by remaining connected to each other as well as through a long period of trusting that others will discharge their own obligations (Blau, 1964; Morris, 2005). Similar to the discussion of Blau (1964) are the comments of Thibaut & Kelley (1959) who suggest that the creation of relational norms may serve in the place of contracts or other legal mechanisms. The elements of relational exchange in marketing channels are strengthened by norms of role integrity, relationship preservation, and harmonization of conflict (Brown et al., 2000).
It can be shown that many of the most significant postulations from exchange theory provide insight into interactions among firms. The tenets of social exchange theory state that interactions involve trust and that, as the interactions increase, relationship continuity is engendered. This notion can be further explained by Dwyer et al. (1987) who present a model to illustrate buyer-supplier relationships along the transaction- relational continuum. Dwyer et al. (1987) comment that when the levels of net expected benefit are high in absolute terms for both partners, “bilateral relationship maintenance” occurs and so both actors work to maintain the relationship.
Much of the B2B marketing literature regarding relational exchange theory has been posited in earlier times, and criticisms of exchanges in fully understanding inter-firm interaction have been made. Dwyer et al. (1987) believe that the relationship aspect of exchanges has been neglected in the literature, particularly the dyadic perspective of relationships, and that there needs to be a greater emphasis on investigating the benefits and the effect of ongoing relationships. The concept of ongoing, dyadic relationships is therefore, the area of discussion in the next section.
2.4.3 Relationship development and relationship marketing B2B marketing literature discusses the ways in which firms exchange products and socially interact in exchange episodes. These premises were discussed earlier. Criticism has been made that the relationships between actors has been neglected. For example, Ravald & Gronroos (1996) discuss the shift in discussion to the focus on relationships whereby inter-firm loyalty enhances profitability and a long term relationship is engendered. In “close” relationships, the buyer, rather than just evaluating the product being exchanged, evaluates the relationship. Future purchases from a supplier are not purely based on the attributes of the product being offered, or whether the product is
22 exactly what is required, but also on whether the buyer wishes to maintain the relationship. Ravald & Gronroos (1996) focus on relational behaviour, not just during the length of the relationship, but during the episodes of the relationship such as when the product is being purchased. Ravald & Gronroos‟ (1996) premise is that the purchasing decision during this episode is not only driven by the core product benefits but also by the willingness to maintain the relationship.
The concept of B2B marketing focusing on relationships rather than exchanges is further discussed by Dywer et al. (1987) who comment that exchanges do not fully conceptualise inter-firm interaction and that relationships are rooted in the idea of relational contracts whereby the effect that is associated with the social interaction between firms is important and both parties make an effort to maintain a relationship that contains healthy social interaction. Dwyer et al. (1987) further discuss the concept of relationships by describing a process whereby relationships develop. Dwyer et al. (1987) discuss five stages of relationship development: awareness of a need to create a relationship, exploration for firm partners based on product needs and relational compatibility, expansion of the relationship into further products and subsequent orders, commitment to the relationship, and dissolution of the relationship. Anderson (1995) critiques the relationship development process of Dwyer et al. (1987) by stating that, although the process involves stages, it is very linear in fashion. Anderson (1995) argues that relationship development is a continuous process, but is remembered by managers and business owners as a series of exchange episodes that involved personal experience. Each of these episodes gives the firm a positive or negative appraisal of the firm, and after each episode the firm can decide whether to continue the relationship at the same level of collaboration, to broaden it, or to cease it. This approach focuses on the exchange process discussed previously whereby the firms focus on exchanges and the benefits derived from them (Bagozzi, 1975; Frazier, 1983).
Further to the discussion of Dwyer et al. (1987) and Anderson (1995) is the premise posited by Wilson (1995) that relationships develop over time; however, the development contains various relational variables within the process. Wilson (1985) discusses a 5 stage process which contains:
1. partner selection which is based on variables such as reputation, social bonds, mutual goals, trust and power; 2. a definition of the purpose of the relationship which is based on trust, social bonds and mutual goals; 23
3. setting relational boundaries based on adaptation, power, mutual goals; 4. the creation of relational value based on cooperation, commitment, structural bonds; and 5. relationship maintenance, based on commitment, mutual investment and adaptation.
Based on the notion of relationship and relationship development is the concept of relationship marketing. The tenet of relationship marketing is that greater cooperation between buyers and suppliers creates competitive success (Morgan & Hunt, 1994). The relationship marketing process involves four stages:
1. deciding on customer accounts (involving considerations for profit potential); 2. developing account-specific offerings (i.e. product offers specific to the partner); 3. implementing relationship strategies; and 4. evaluating relationship strategy outcomes (for performance and changes in customer needs). (Hutt & Speh, 2010).
The tasks involved in the relationship marketing process include the problem of allocating resources to different relationships and managing interactions within each relationship (Håkansson et al. 1976; Ford, 1980). In such a way, a winery would develop different ways of interacting with growers in the process of obtaining grapes. Concepts of relationship marketing are more than just cooperation between two parties and refer to relationships in a more personal and less transactional manner. Relationship marketing is also grounded in social exchange theory, the premise of which is that parties enter into long-term relationships in order to gain additional benefits. Relationship marketing and relationship development literature has shown that interaction between firms is more than episodic or discrete for the purpose of obtaining product and the interaction is also social in nature.
Further discussion has also considered the interaction between firms which is fashioned like a network. This is discussed in the next section.
2.4.4 Business to Business networks Firms interact with each other in order to gain products which can be sold onto other supply chain members and ultimately are consumed by end users. Prior discussion has
24 focused on the exchange and relational perspective of inter-firm interaction. However, inter-firm interaction can also be discussed from a network perspective. This perspective has been advocated by the Industrial Marketing and Purchasing (IMP) group who view inter-firm interaction from a network perspective (Håkansson & Snehota, 1995; Simon et al., 2003). Put simply, the IMP perspective is rooted in the notion that firms are interconnected, particularly in terms of the activities performed by each actor, and the resources which are utilised and obtained to facilitate the relationship (Simon et al., 2003). The interconnectedness of all the firms creates a network that not only facilitates the movement and purchasing of product but also the psychosocial interaction between the firms (Simon et al., 2003). The IMP perspective also posits that networks are an efficient form for organising business activities and that there is something to gain from operating in a network rather than being a “lone ranger” in the market. This notion is further developed by Geersbro & Ritter (2010) who comment that due to the network-like behaviour of the inter-firm interaction, the relationship is not under the control of one firm in the interaction but by bilateral interaction between firms. However, business networks can enable or hinder firm performance (Håkansson & Ford, 2002) as the network allows actors to gain connectedness and share networks that allow for the creation of efficiencies that lead to customer satisfaction, but can also hinder efficiency due to the potentially large number of parties in the network which can cause conflict to arise because the connectedness becomes too complex and the interests of individual firms are forgone in the interests of the network.
The IMP perspective also discusses the notion of “ingredients” that create and sustain the network, similar in fashion to the exchange and relationship process development of Frazier (1983) and Dwyer et al., (1987). Ford et al., (2003) state that networks consist of three variables:
1. bonds between actors, which evolved over time through activities such as purchasing and buying, and such as social bonds rooted in personal relationships. These bonds are enhanced due to the interdependence that results from close knit networks; 2. resource ties, such as investment in resources to aid the networks such as IT systems to improve communication across the network .These resources are embedded in the network and are adapted for the purposes that are needed (Lusch & Brown, 1996); and
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3. activities of network members that are fashioned in a way to gain maximum benefit to the network as a whole, such as which firms will be involved in activities such as logistics, information dissemination and manufacture.
The benefit of the network perspective to individual firms can be viewed in the following way: by having a high quality relationship with other firms in the network, investing in resources to gain access to another firm, and by being effective and efficient in the activities they perform in the network, a firm can gain a strong “network position” that will lead to its success and profitability (Ford et al., 2003).
This is particularly true in the wine industry where the strength of the grape grower, in growing grapes, and the strength of the winery, in processing those grapes into wine, ensures that a wine product is made that results in a monetary compensation to the grower (for their grapes). Therefore, the grape grower gains from the relationship by gaining monetary compensation and the winery gains by having a product which is fit for market, can be sold, and thus the winery also gains monetary compensation.
The obtaining of benefits from a mutually rewarding relationship is, of course, not automatic. Management of supplier/buyer relationships is necessary to gain from the relationship. Links between the buyer‟s operations and those of the supplier can be adapted to improve efficiency and performance. Furthermore, firms may choose to combine resources such as facilities, equipment or operations in order to strengthen ties with a trading partner (Ford et al. 2003). Over time, the development of actor bonds may create continuity of the relationship (Wilson, 1995). These actor bonds have most commonly been characterised by relational elements such as commitment. Commitment is an implicit or explicit pledge of relational continuity between exchange partners that occurs at an advanced stage of the relationship (Dwyer et al. 1987). The literature discussing commitment focuses on the notion that it only exists in successful relationships that are high in levels of satisfaction and contain solidarity and cohesion (Dwyer et al. 1987; Gundlach et al. 1985).
Commitment to a relationship is not only denoted by the level of investment, over time, made by each party, such as investments in capital items that facilitate the transfer of goods and services such as logistics systems, but also the amount of time given to maintaining the relationship and the salespersons allocated to the relationship (Ford, 1984; Dwyer et al., 1987; Gundlach et al., 1995). Relationships that have high levels of commitment exhibit behaviours from the actors, referred to as relational norms
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(Gundlach et al. 1995). For example, relationships that are high in commitment exhibit lower levels of relational norms such as opportunistic behaviour and higher levels of adaptation (Mohr & Spekman, 1994; Gundlach et al., 1995). Therefore, actors that are involved in highly committed relationships not only make a high level of investment in terms of time and resources but also forgo short term goals for long term benefits and in turn are less likely to engage in opportunistic behaviour (Mohr & Spekman, 1994; Gundlach et al., 1995).
Business networks can provide other benefits through the social interaction that occurs between members of the networks (Benson-Rea, 2005). The interaction between members of these networks can provide each member with information that allows each firm to find new markets which in turn allows for information concerning new products and assists with new product development (Blankenburg-Holm et al., 1996). As such, these social interactions can aid the businesses in finding new markets and market expansion, thereby assisting in business profitability and sustainability.
While business relationships differ depending on whether they are exchanges, dyadic relationships or part of a network, the relationship outcomes will ultimately affect each other (Mandjak & Simon, 2004). This empirical study addressed a gap through the development of a theoretical model to conceptualise and measure the effect that specific relational norms have on relationship quality created through trading relationships between buyers and sellers of wine grapes in Australia. The model viewed the suppliers‟ (grape growers‟) perspective of the relationship, as it is considered that this actor plays the most vital role in the production of wine.
This study focused on a specific relational norm of communication (namely, a theory of collaborative communication) and how it affected quality in the relationship. Development of the theoretical framework entailed the selection of relational norms which reflected the interaction between the two actors and observed the effect that environmental influences (such as power asymmetry) had on exchange behaviour (Håkansson, 1982). A number of exploratory in-depth interviews with grape growers were conducted to ensure that the selected relational norm (collaborative communication) and power asymmetry were relevant to trading relationships in the Australian grape and wine industry.
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The next section of this chapter discusses the relational norms evident in business to business relationships which were tested on grape growers in the exploratory stage of the study to gain an understanding of their appropriateness for the conceptual model.
2.5 Relational norms Although many researchers have used various ideas for conceptualising relational behaviour constructs, the relational contracting theory is relatively comprehensive (MacNeil, 1978; Dwyer et al., 1987; Heide, 1994). MacNeil (1978) posits that formal contracting is but one of the mechanisms to govern business relationships and that exchange partners will develop joint expectations about what behaviours are appropriate in order to complete formal arrangements (Heide, 1994). The relationship is thus governed by certain expected behaviours, namely relationship norms (Thibault & Kelley, 1959; Heide & John, 1992). Furthermore, the general property of the relational norm is the prescription of behaviours that aim at maintaining a relationship and their rejection of behaviours that promote individual goal seeking (Heide & John, 1992). In evidence of this, Ivens (2004, p 301) has argued that “…every norm refers to a potential behaviour and the norm framework may be used as a structuring scheme for research on relational behaviour”. The literature has highlighted numerous relational norms and Table 2.1 shows a number of relationship norms as summarised by Ivens (2004) from other relationship literature.
Table 2.1 exhibits a synopsis of the literature regarding relational norms. The table provides an overview of the various norms and it would be of interest to observe which set of norms is applicable to the Australian wine industry and the grape grower/ winery relationship. Furthermore, the relational norms are “building blocks” of the relationship and as such must be viewed in terms of their effect on a whole relationship. Of particular interest is the relational norm of communication.
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Table 2.1: List of relational norms Norm/behaviour Description
Cooperation The coordination tasks which are undertaken jointly and individually to pursue common and/or compatible goals and activities undertaken to develop and maintain the relationship (Young & Wilkinson, 1997; Leonidou et al (2002, 2006); Woo & Ennew, 2004)
Social bonds A personal relationship resulting from the economic exchange that can be linked to social bonds which are a “glue” that holds the individuals together (Turnbull & Wilson, 1989; Bendapudi & Leone, 2002)
Communication Readiness to proactively provide all information useful to the partner (Mohr & Nevin, 1990; Heide & John, 1992; Lusch & Brown, 1996; Mohr et al. 1996)
Solidarity The preservation of the relationship particularly in situations in which one partner is in a predicament (Kaufmann & Stern, 1988; Achrol, 1997)
Flexibility Actor‟s readiness to adapt to an existing agreement (implicit or explicit) or to new environmental conditions (Nordewier et al. 1990)
Conflict resolution The use of personal, friendly and informal mechanisms to resolve conflicts (Kaufmann, 1987)
Cultural fit Understanding of partners‟ attitudes and behaviours and appropriate interpretation of actions (Gyau & Spiller, 2007)
As previously discussed, the two wine industry actors must liaise during the growing season to create a grape product fit for their purpose. To do so, the two actors must communicate to convey the necessary information, particularly in regard to grape parameters such as sugar content, berry size and residual chemical content that results from the use of pesticides and herbicides (Clancy, 2005). Communication is performed via various modes (e.g. face to face, electronic, telephone, seminars, newsletters etc). It 29 is of interest to observe how these different modes and their frequency influence grape growers‟ perceptions of relationship quality. Furthermore, it has been highlighted in wine industry trade literature that communication between grape growers and wineries is important (Spawton & Walter, 2003; Chong, 2007; Hobley, 2007; Brown, 2008). Discussion on the literature regarding communication is warranted and is the topic of discussion in the next section.
2.6 Communication Communication is important in establishing objectives and coordinating activities to meet those objectives (Mohr et al., 1996). Much of the literature discusses the effect that specific dimensions of communication have on the relationship (Mohr et al., 1996) and the openness of the information (Heide & John, 1992), and is of particular interest to this study whereby relational norms have an effect on relationship quality.
Communication frequency is a dimension of communication that requires observation. Daft & Lengel (1984) suggest that the modes of communication differ in their fertility and their ability to convey information, and that richer modes of communication (such as face to face) allow for more tailored communication (specific to the circumstance) and allow for immediate feedback. Daft & Lengel (1984) also discuss written and electronic forms of communication as being less “rich” and more useful in communicating large amounts of homogeneous information. Given these observations it is of interest to observe how these various modes and dimensions affect relationship quality.
From a winery perspective, these communication modes have varying degrees of cost. Cannon & Homburg (2001) comment that richer modes are more costly, but also concede that the effectiveness and efficiency of communication must be matched with the mode. With respect to the efficiency of communication, Daft & Lengel (1984) state that complex, unstandardised information is best communicated by rich modes (for example face to face) as opposed to less important more “mechanical” information that is best transmitted via less rich modes such as written or electronic. Furthermore, less rich modes of communication (such as written or electronic) can supplement the rich forms (for example face to face), particularly if the supplementary information is self- explanatory and does not require a rich description from the sender (Cannon & Homburg, 2001). In regards to the specific frequency of the mode of communication,
30 an increase in frequency produces a greater volume of communication to be transmitted, hence improving the understanding of the problem faced by the supplier (O‟Neal, 1993).
Associated with the notion of communication is information sharing. This is defined as the extent to which the supplier shares information with the buyer and this can lead to a fruitful relationship with the buyer if the information leads to a lowering of costs and greater relational efficiencies that result from understanding future plans of the supplier and the coordination of production development (Anderson & Narus, 1990; Cannon & Homburg, 2001).
Further to the notions of frequency and modality of communication is the multi- dimensional nature of collaborative communication as proposed by Mohr & Nevin (1990). Mohr & Nevin (1990) propose that communication has facets beyond frequency and modality and includes such aspects as the formality of the communication (whether communication is formal or informal), its bi-directionality (whether the communication flows only from one actor or from both i.e. in both directions of the relationship), and indirect influences of communication (whether the communication indirectly affects the activities of the partner). From a wine industry context, the importance of communication between actors has been identified as an issue (Spawton & Walter, 2003; Chong, 2007; Brown, 2008). Hobley (2007) has shown that communication is an important relational dimension in the Australian industry; this is also an important issue in other countries‟ grape grower/ winery relationships. Redondo & Fierro (2007, pg 86) discuss this issue from the Spanish wine industry context where it was found that increased communication makes the relationship “continual” and resulted in greater levels of satisfaction for the actors. Brown (2008) added that communication between grape growers and wineries is of major importance to the success of individual grape relationships, with Chong (2007) further adding that a greater understanding and refinement of communication and information systems is needed in the industry.
This discussion regarding communication has illustrated the multi-dimensional nature of the communication construct, including the nature of information sharing, its overall effect on the relationship, and its importance in the Australian wine industry context. Therefore it would be of interest to identify the modes, frequency, formality, bi- directionality and influence of communication from a grape grower‟s perspective and to observe how these dimensions influence relationship quality. 31
2.7 Relationship quality While relationship norms and variables can be considered building blocks of the relationship, the quality of the relationship is also an important factor which can be observed. Relationship quality refers to a supplier‟s perception of how well their relationship fulfils his expectations, predictions, goals and desires (Gyau & Spiller, 2007). According to Wong and Sohal (2002), relationship quality conveys a customer‟s impression about the whole relationship and, as such, is manifested in several distinct but related constructs. However, there seems to be no consensus among researchers on the set of constructs or variables that constitute relationship quality (Crosby et al., 1990; Ceceres & Paparoidamis, 2007; Gyau & Spiller, 2007).
In spite of the fact that researchers conceptualize relationship quality with dissimilar dimensions, they appear to concur generally that relationship quality measures actors‟ awareness of how well their relationships with their partners fit, and is often connected to a firm‟s ability to sustain their relationships in the long-term. Ceceres & Paparoidamis (2007, p 837) affirm that “…there is general agreement in the relationship marketing literature that the quality of the relationship between the parties involved is an important determinant of the permanency and the intensity of the relationship and the consequent success of relationship marketing practices”.
Studies involving relationship quality draw heavily upon the social psychology literature. Unlike relational norms and elements (such as social norms, flexibility and shared goals) which are uni-dimensional constructs measured in a uni-dimensional fashion (e.g. the trust construct is measured via latent variables concerning trust); the literature discusses relationship quality as a multi-dimensional higher order construct that consists of trust and satisfaction. Crosby et al. (1990) discuss the relationship quality as being comprised of trust and satisfaction and argue that if a partner can be relied upon to fulfil his duties in the interest of the relationship, then satisfaction will occur. Wray et al. (1994) and Lagace et al. (1991) affirm this notion, and add that trust helps in allowing tensions to be resolved which results in satisfaction for the partner. This alludes to a notion that trust is an antecedent of satisfaction and relationship quality, although the literature has not confirmed this notion. Kim & Cha (2002) and Kim et al. (2006) for instance, conceptualise the relationship quality construct as indicative of the level of satisfaction and do not discuss the influence of trust; however, their comments oppose those of Dwyer et al. (1997) that commitment is not a measure 32 of relationship quality but a predictor or outcome of it, whereby trust in a partner and satisfaction in the relationship leads to commitment. Therefore, Kim & Cha (2002) and Kim et al. (2006) allude to the fact that relationship quality is an antecedent of commitment and further add that relationship quality is a higher order construct that reflects the strength of the relationship. Other researchers, such as Gummeson (1987), Leuthesser (1997), Dorch et al. (1998), Naudé & Buttle (2000) and Parsons (2002), further argue that relationship quality is comprised of trust and satisfaction. However, Scheer & Stern (1992) and Leuthesser (1997) empirically tested relationship quality as a uni-dimensional construct whereby the construct of relationship quality consists of the latent variables of trust and satisfaction. Given the framework that has been adopted for study, and the prevailing emphasis in the literature linking trust and satisfaction to relationship quality, the author has conceptualised relationship quality as a measure of trust and satisfaction.
The preceding literature discussed whether relationship quality is a multi-dimensional construct comprised of trust and satisfaction; however, there have been two instances where relationship quality has been judged to be a uni-dimensional construct (see Scheer & Stern, 1992 and Leuthesser, 1997). Crosby et al. (1990), Dorch et al. (1997), Kim & Cha (2002) and Kim et al. (2006) empirically test relationship quality, mostly via SEM and other multi-variate regression techniques, and use trust and satisfaction as separate constructs; they discuss whether higher levels of trust and satisfaction in their model correspond with higher levels of relationship quality.
This notion has been applied to this study and is discussed further in Chapter 6. However, an alternative estimation of relationship quality, based on a uni-dimensional measurement, has also been performed in this study and is further discussed in Chapter 3, section 3.12. Regardless of the estimation technique, the literature has shown that relationship quality is comprised of trust and satisfaction.
2.7.1 Trust as a dimension of relationship quality Trust is defined by Zaheer et al. (1998, p 21) as the principle that the business partner “can be relied upon to fulfil obligations and behave in a predictable manner”. However, trust is not attainable in the short-term. Blau (1964) commented that trust is the result of
33 repeated exchanges between two organizations. Houston & Gassenheimer (1987, p 10) affirm this statement and add that trust between two parties “…leads to a long term relationship”. Trust also decreases risk, particularly as it can act as an “…information resource that reduces the threat of information asymmetry and performance ambiguity” (Batt, 2003 p 66). Trust also results from the expertise, reliability or intentionality of the partner, and can be built by the competence, honesty, dependability and likability of the partner (Batt, 2003). From an SME context, trust has been shown as an important ingredient in the creation of partnerships, strategic alliances and networks (Brusco, 1986; Smitka, 1991; Powell, 1996). Additionally, Sako (1997) viewed trust from three perspectives, namely contractual, competence and goodwill trust. Contractual trust is concerned with the extent to which parties can carry out their contractual obligations. Competence trust relates to the understanding of professional and technical standards, and goodwill trust denotes that the relationship has a degree of fairness related to practices. Adding to Sako‟s (1997) discussion of trust perspectives, Kumar et al. (1995) discuss that trust has two elements:
1. trust in the partner‟s honesty and the belief that the partner will stand by his word and fulfil his obligations and is sincere; and 2. trust in the benevolence of the partner in that the actor is interested in the welfare of the partner‟s firm and won‟t work to take actions that will negatively affect that firm.
Trust in relationships also has many benefits for each firm. Relationships that contain trust will also be better able to manage conflict within the relationship and a greater degree of adaptability to the other firm‟s requests will occur (Mohr & Spekman, 1994). Once trust is evident in a relationship, the actor understands that joint efforts will lead to outcomes that exceed what could have been achieved if each firm acted solely in their own interests (Mohr & Spekman, 1994). Conversely, a lack of trust in a relationship can lead to decreased relational norm effectiveness such as a decrease in communication quality and the ability to jointly solve problems when they occur.
Trust is also developed in a relationship over time and it has been shown that trust is an antecedent of commitment (Morgan & Hunt, 1994). Furthermore, evidence that trust is being developed in a relationship is shown if:
1. an actor is willing to customise their equipment and processes to the other actor‟s requirements;
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2. actors are willing to share confidential information; and 3. in line with the discussion of Morgan and Hunt (1994), are willing to engender a long term relationship. (Doney & Cannon, 1997)
2.7.2 Satisfaction as a dimension of relationship quality Satisfaction refers to a positive affective state resulting from the appraisal of all aspects of a firm‟s working relationship with another firm. Satisfaction is important to the long term success of the firms involved in a working relationship and therefore encourages a long-term relationship and relational continuity (Oliver, 1980, Anderson & Narus, 1990; Ganesan, 1994). Various dimensions of the BS relationship have been discussed, particularly how intensity affects the relationship quality. If the intensity is low, the relationship quality is poor; however, satisfaction is a consequence of a positive relationship. Batt (2003) describes satisfaction as occurring when performance exceeds expectations. Oliver (1980) further describes satisfaction as a result of an evaluation between the partner‟s performance and the firm‟s expectations. Further studies show that satisfaction positively enhances trust (Mackenzie & Hardy, 1996) with Geyskens et al. (1999) arguing that if the channel members are highly satisfied, the partners believe them to be more trustworthy. However, satisfaction‟s influence on trust is not easily attained. Batt (2003, p 69) states that “…satisfaction with an exchange will lead to some initial trusting behaviours, but as satisfaction increases, trust will increase”. Fornell (1992) further adds that satisfaction is evident in quality relationships and is cumulative over time and based on experiences.
Satisfaction has been discussed as a function of expectations in the partner firm‟s performance (Oliver, 1980). The perception of the performance leads to post-purchase satisfaction; however, Anderson & Narus (1990) warn that satisfaction as an area of academic research is fraught as it is a highly subjective construct. Anderson & Narus (1990) discuss satisfaction as being linked to perceptions of influence; if a firm believes they have greater influence over their partner, they experience higher levels of satisfaction. This appears to relate to power asymmetry whereby the actor which has the higher level of power has greater satisfaction, although Anderson & Narus (1990) do not comment on this. Anderson & Narus (1990) do add that relational norms will affect satisfaction, that conflict and disagreements between firms will block goal attainment
35 and lead to decreased satisfaction, and that cooperation and mutual goal attainment positively affect satisfaction.
As previously discussed in wine industry trade literature, relational norms such as power asymmetry are having a great effect on grape grower and winery relationships in the Australian wine industry and, as power asymmetry is a relational norm, this will have an effect on relationship quality. This is highlighted in the next section.
2.8 Power Asymmetry As noted earlier, wineries in the Australian wine industry have been cancelling supply contracts and not maintaining business relationships due to an oversupply of grapes. The cancellation of contracts is a result of power asymmetry.
Power asymmetry is not uncommon in the wine industry. Discussed in Chapter 1, there are incidences of power asymmetry disrupting and potentially harming grape grower and winery relationships such as is evident in Kosovo and France where this has led to protests and violence (Phillips, 2000). Power asymmetry in these countries was attributed to a lowering of the grape harvest as a result of pressure further up the wine supply chain, such as supermarkets discounting imported wine products or decreasing exchange rates. The exchange rate decreases resulted in decreased revenue for wineries, which in turn created cost pressures for wineries; they alleviated these pressures by offering lower grape price (Phillips, 2000).
However, there is also evidence in the wine industry of the effects of the power asymmetry being felt by the wineries; in this case the grape grower holds the power in the relationship. This appears to be the case in wine regions where grape products are in high demand. This phenomenon is documented by Redondo & Fierro (2007) whose study on the Somontano wine region in north western Spain examined a region where grape produce was in high demand and therefore where grape growers attained power over the wineries and could demand higher prices. Charters & Menival (2010) showed a power asymmetry favouring grape growers due to wineries wishing to maintain high quality in their products from the Champagne region; grape growers had a level of power over wineries and could dictate terms. This was exacerbated by the fact that there was a shortage of grape growers in Champagne due to geographical restriction. Therefore, in the study of Redondo & Fierro (2007), grape growers gained power due to 36 a scarcity of their product, while in the study of Charters & Menival (2010) grape growers‟ gained power because there was only a small population of grape growers, and the wish of wineries to maintain quality standards was only possible by rewarding grape growers who produced high quality grapes.
While power and power asymmetry is documented in the wine industry, it is also evident in academic literature. By definition, power is the ability of one actor to influence another to act in a manner that he/she would not have otherwise chosen (Emerson, 1962). Cox et al. (2003) contribute to the discussion by arguing that buyer/seller relationships are driven by the power maintained by one organisation which is willing to take whatever action is necessary to maintain that dominant position.
Cox et al. (2003) further identify four main power structures in the literature: dominance, interdependence, independence and dependence (Cox et al. 2003). Thibaut and Kelley (1959) explore the issue of both coercive and constructive conflict in impersonal relationships, and this was applied in a business to business context by Ford (1984), who argued that all inter-organisational relationships exhibit conflicts and cooperation simultaneously and that the two are not mutually exclusive. Power has also been attributed to conflict in a distribution channel with the nature and origin of the power that the channel member possesses influencing possible conflict (Gaski, 1984). However, while creating conflict, power has also been viewed as a “moderating power”, alluded to by Ford (1994), whereby the power allows for conflicts and cooperation to exist simultaneously. Reve & Stern (1979) mention that power is used to organise the channel member and also to ensure that conflict stays manageable. The power in the channel is confirmed by Seyed- Mohamed & Wilson (1990) who mention that the greater the degree of threats made by the buyer, the greater the amount of disturbance that exists in the relationship. Operationally, the seller wishes to have his/ her products purchased; thus, if the seller is dependent on the buyer, the buyer will have the power in the relationship thereby creating a power imbalance (Wilson & Vlosky, 1998). Anderson & Weitz (1989), Ganesan (1994) and Varadarajan & Cunningham (1995) pointed out that in a situation of power imbalance, the party with the higher level of power will try to exploit its advantage in such a way that the other party becomes dissatisfied with the relationship. This is prevalent in the Australian wine industry, where the winery has the power to accept or decline the supply of grapes from grape growers and can use their dominant position to demand certain requirements from grape
37 growers. This is exacerbated in a scenario where the seller has a limited number of buyers to select from, which is evident in the current Australian grape grower/winery relational circumstance. Therefore, the relational norm of power asymmetry is affecting relationship quality.
The preceding discussion regarding relational norms, in particular communication, power asymmetry and relationship quality, has been linked to current dilemmas in the Australian wine industry.
2.9 Literature Discussion This chapter has discussed literature in the B2B marketing and inter-firm behaviour area. It has also combined both academic and wine industry trade literature in order to understand the background to a problem. The purpose of the chapter is to highlight the nascent literature in the domain of business to business marketing and purchasing which occurs between grape growers and wineries, the context for this study.
The chapter has shown that unlike purchasing in consumer markets, the decision making process used to identify which products should be purchased is far more complex in business markets. Furthermore, the volume of product purchased in B2B markets is far greater than in B2C markets and the time and effort exerted in B2B purchasing is great due to the importance of the process to firms (Kotler et al., 2010). Similarities can be shown between purchasing decision processes in consumer and business markets, though a greater level of time and resources is used in the latter (Moriarty, 1983; Johnson & Lewin, 1994; Ford et al., 2002). With regard to the actual purchasing of product in a B2B context, firms coordinate various intra-firm departments and activities (such as logistics, finance, manufacturing); however, what sets it apart from consumer markets is the level of decision making and the process of decision making whereby buying centres are used to deliberate over and coordinate the process (Ozanne & Churchill, 1971; Webster & Wind, 1972; Bradley, 1974), the main aim being to gain consumer satisfaction (Porter, 1985). In effect, purchasing has a process and function perspective whereby processes are performed to gain product, and many functions of the business are coordinated to facilitate this process.
However, this concept of purchasing is highly focused on intra-firm activities and does not comprehend fully the concept that firms interact in the purchasing process. Earlier literature discusses inter-firm relationships as social exchanges whereby the exchange 38 has numerous elements conceptualised as relational norms such as cooperation, solidarity and social bonds that are built by the parties and maintained in order to maintain the relationship and to reduce transaction costs and resource misallocation that results from discrete relationships (Thibault & Kelley, 1959; Wilson, 1995). This discussion is based on the concepts of relationship marketing and social exchange theory which are generally based on the notion of a dyadic relationship whereby two parties interact in a relationship.
The concept of a relationship in B2B markets is further developed by the IMP group who argue that relationships are more than dyadic and involve networks in and around the firms; this can involve numerous firms which support the activities of the relationship (Hakansson & Snehota, 1995; Ford et al., 2003; Simon et al., 2003; Geersbro & Ritter, 2010). As numerous firms are involved in the network, each makes high levels of investment of capital resources and time to establish and maintain themselves in the network. In well run networks, relational norms such as cooperation, communication, social bonds and flexibility are in existence at high levels and help to maintain the network with actions such as opportunistic behaviour being discouraged as it impedes other firms within the network and so is detrimental to it (Ford et al., 2003; Simon et al., 2003).
Of interest to this study is the relational norm of communication. It has been described as the glue of a relationship, and has been discussed by wine industry literature as being highly important to grape grower and winery relationships and to the wine industry as a whole (Spawton & Walter, 2003; Chong, 2007; Hobley, 2007; Brown, 2008). From an academic literature perspective, Mohr & Nevin‟s (1990) collaborative communication theory states that communication has various elements such as formality, frequency, non –coercive communication attempts and bi-directionality, and that this theory has not been tested in a wine industry context.
While exchanges, relationships and relationship networks act to facilitate the flow of product through the marketing channel, the outcome of the relationship is important, particularly the perception of the quality of the relationship that an actor has. The chapter has discussed the theory of relationship quality and shown that a high quality relationship contains high levels of trust and satisfaction and vice versa (Gummeson, 1987; Leuthesser, 1997; Dorch et al., 1998; Naudé & Buttle, 2000; Parsons, 2002). While the discussion of the B2B literature has contained various theories and concepts of importance to the wine industry, trade literature has shown the relational norm of 39 communication (Spawton & Walter, 2003; Chong, 2007; Hobley, 2007; Brown, 2008) and power asymmetry (Phillips, 2000; Redondo & Fierro, 2007; Charters & Menival, 2010) affect the wine industry and should be observed. This is the underlying premise of this study.
Mohr & Nevin‟s (1990) theory of collaborative communication has not been studied in the wine industry context and from an academic perspective how the elements of collaborative communication affect relationship quality or the affect that power asymmetry has on relationship quality, has not been studied either.
In summary, based on concepts taken from academic and wine industry trade literature, this study will attempt to examine how collaborative communication elements and power asymmetry affect relationship quality. This has not been studied previously either in an academic context or in a wine industry context, and has been highlighted in the wine industry literature as being important.
2.10 Chapter conclusion This chapter detailed literature pertaining to B2B marketing, particularly related to communication, power asymmetry and relationship quality. The next stage of the study, the exploratory stage, involves qualitatively testing (by way of in-depth interviews with grape growers) these concepts to understand the effect these elements (i.e. communication, power asymmetry and relationship quality) have on their perception of the relationship.
The exploratory stage is followed by the descriptive and causal stages in which the results from the exploratory stage are quantitatively tested (via a questionnaire). However, before the results of the exploratory stage can be presented, the methodology of how the data collections were performed will be discussed and both provide the topic of the next chapter.
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Chapter 3: Exploratory research methodology and results
3.1 Chapter introduction The first chapter of this dissertation outlined the Australian wine industry rationale for the study, including the current economic state of the industry, and defined research objectives and problems related to this study. The previous chapter (Chapter 2) provided a theoretical background to the research objectives and problems by highlighting the relevant literature in relation to B2B interactions and marketing. Further investigation was required to verify the effect that power asymmetry and Mohr & Nevins‟ (1990) collaborative communication theory had on relationship quality and, as a result, an exploratory research study was required to observe this and create a conceptual model. The opening part of this chapter describes the exploratory research study design, including the methodology used and the objectives of the research study. The concluding sections of this chapter relate to the analysis and results of the study, including the limitations of the study, the definition of hypotheses, and the presentation of a theoretical model.
3.2 Exploratory research design A qualitative research study was used to explore the effects that relational norms, such as communication, and relational elements, such as power asymmetry (as discussed in Chapter 2), have on relationship quality, utilising the South Australian and Victorian wine industries as a context. Such an approach is supported by discussions in the literature that state that this type of methodology is appropriate when a researcher wishes to understand and further develop hypothetical issues raised in the literature, and to make sure that they are applicable to the business context to be examined (Zikmund & Babin, 2007; Leedy & Ormrod, 2010). The qualitative research approach and the information gleaned was critical in understanding the appropriate questions and scale items to be used in the descriptive and causal stages of the study, the quantitative phase of the project. As such, the exploratory, qualitative research approach allowed the author to ascertain whether the issues highlighted in the literature were applicable to the wine industry context, and they allow both for more concrete assumptions to be made
41 and also for the creation of a conceptual model to address the research problems and objectives.
The qualitative methodology employed in this stage of the study was in-depth interviews (IDI). IDI involves conducting one-on-one interviews with a small number of respondents to uncover their opinions on issues that are raised by the interviewer (Boyce & Neale, 2006). This method yields richer information than other methods such as quantitative methods (survey based methods), and other qualitative methods such as focus group interviews (Leedy & Ormrod, 2010, Malhotra et al. 2006). The methodology is also more flexible than other methods such as quantitative ones, as the issues and questions that are posed by the interviewer can be open ended and the interviewer has the option to further explore topics as they see fit (Malhotra et al. 2006). The “one-on-one” nature of the IDI method also allows for confidential information, which can be problematic in other less confidential qualitative methods (such as focus groups) that involve interviewing numerous people at one time, to be discussed (Malhotra et al. 2006). The participants of the IDI in this study were discussing private business relationships that may have involved confidential information (such as contract issues and legal issues surrounding abuses of power asymmetry) and as such, the personal, confidential nature of IDI made them appropriate for this stage of the study.
Thirteen grape growers were recruited for the IDI and were based in South Australia and Victoria. The location of the growers was based on their close proximity to the author. The participants were recruited on the basis of the size of their operation and the nature of the region (in South Australia and Victoria) in which their grape growing businesses were located. This allowed for a participant base with differing production sizes, ranging from professional grape growing businesses to “hobby” style grape growing businesses whose proprietors were less involved in the business by way of time commitment and financial investment. The location and size of the participants are illustrated in Table 3.1.
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Table 3.1: Location and size of grape grower participants‟ businesses
Location Size
McLaren Vale, SA < 10 acres
McLaren Vale, SA 30-40 acres
McLaren Vale, SA 10-20 acres
McLaren Vale, SA < 10 acres
Clare Valley, SA 10-20 acres
Adelaide Hills, SA 20-30 acres
Adelaide Hills, SA < 10 acres
Adelaide Hills, SA < 10 acres
Barossa Valley, SA 40-50 acres
Barossa Valley, SA 20-30 acres
Barossa Valley, SA 10-20 acres
Yarra Valley, Vic < 10 acres
Yarra Valley, Vic 10-20 acres
3.3 Participant sample selection and interview format Of major importance in the planning stage of IDI was the selection of the participants (Malhotra et al. 2006). The business details of grape growers were obtained from the various grape and wine region industry associations (for example, Barossa Valley Vignerons Association, Adelaide Hills Wine Growers Association). The regional associations provided the details of the grape growers (the size of vineyards, location, telephone numbers) and a selection was made to gain a broad cross section of growers with differing production size and quality foci, thus allowing observations to be made on relationships with differing types of wineries (for example, publicly and privately owned, high quality and lower quality production wineries). Even though the results of IDI are not able to be generalised due to the small sample size, efforts were made to maximise the extent to which the participants were representative of to that of the grape grower population in Australia (Boyce & Neale, 2006; Hobley, 2007).
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The participants, as detailed in Table 3.1, differ in their production foci and quality foci. They are based in warm and cool climate regions with sizes that would indicate that they produce grapes that are lower or higher in quality. This allowed for responses that would be more easily generalised to the target population (i.e. grape growers in Australia). The participants were recruited by telephone, as this was deemed an appropriate way to make contact with the most suitable interview candidates due to their disparate location which made personal contact via travelling and meeting unsuitable (Malhotra, 2006). The reason for choosing the participant, the duration of the interview, the structure of the questions, the type of questions to be posed in the interview, and details of how the information obtained would be kept in confidence, were all discussed in the initial telephone call. A time and a place for the interview was agreed upon, with all but two interviews taking place in the participant‟s place of business. The other two interviews took place at the home of the participant in a quiet and secure room.
In terms of the participants‟ activities and responsibilities within the grape growing business, the participants recruited had to be the principal owner or manager of the business with responsibility for the decisions regarding which winery to sell their grapes to, and to have managerial responsibility over the other employees of the business. Therefore, in all cases, the participants were either the owner of the grape growing business or the managing director of the business. In terms of Webster & Wind‟s (1972) criteria for roles in decision-making in a business, the participants had to satisfy the „decider‟ criteria for decision making. Consequently, the grape grower (supplier) selected as a participant in the study were required:
to have significant experience with dealing with wineries in the trading of wine grapes; and to be involved in a grape growing business that is generally representative of the wine-grape growing population.
After consultation with wine industry experts (Davidson, pers. com., December 2008, Mckenzie, pers. com., December 2008), it was decided that owners or managing directors of the grape growing business were the appropriate participants for the exploratory study.
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3.4 Structure of the interview format Each IDI commenced with a statement by the interviewer that the information gleaned from the interview would to be kept in strict confidence. The participant was also asked to consent to the use of an audio recorder that was used to record the interview for later analysis. Participants were also reassured that the audio recording would not be exhibited to any other persons and would be used strictly for the study. All the participants agreed to the requests regarding the confidential nature of the recording.
Each IDI‟s duration was 45 to 90 minutes. The variations in the time of each interview were mainly due to the time away from work that the participant could allow; however, all topics were discussed by each of the participants.
While the nature of IDI was unstructured and free flowing, questions were devised to give the interviewer a direction from which to inquire. Structured questions were posed to the respondent to allow for the information required for the research objectives and questions to be attained (Malhotra et al. 2006). As such, the questions were based on issues highlighted in the literature.
A copy of the questions are shown in Appendix 3. All the questions were open-ended in style, allowing participants to answer in their own style and to express opinions. However, prompt questions were also devised so that the participants‟ answers did not go too off the topic and become irrelevant to the study (Cavana et al. 2001; Malhotra et al. 2006). The questions in the interview were based around the research objectives which are discussed in the next section.
3.5 Research objectives The objectives of the exploratory, qualitative study were to explore the nature of the effect of Mohr & Nevin‟s (1990) collaborative communication theory, and the effects of power asymmetry on perceived relationship quality of grape growers. While the free- flowing nature of the interviews was crucial to gathering relevant information, questions (as discussed in the previous section) were posed based on the literature, as it was deemed that communication was an important relational norm between grape growers and wineries in the Australian wine industry. Furthermore, it was identified in the literature that a power asymmetry favouring wineries was affecting grape growers‟ perceptions of relationship quality. The questions were based on the overall objectives
45 which were required to aid in the development of a conceptual model. Therefore, the research objectives were to:
1. uncover the extent to which Mohr & Nevin‟s (1990) collaborative communication elements affect wine grape growers‟ perceptions of relationship quality; and
2. identify the extent to which power asymmetry was affecting grape growers' perceptions of relationship quality.
3.6 Audio transcription and data analysis technique Audio recordings were converted into a digital audio file by the recorder and the audio file was uploaded into a computer. The audio file was then uploaded into computer software named HyperTRANSCRIBE. HyperTRANSCRIBE allowed the researcher to play a section of the audio file into headphones and then type the words into a word processing document. Notepad software was used as the word processing document. Each speaker in the audio file was identified in the transcript. For example, if the interviewer was named Frank, an “F” was placed in front of the words Frank spoke. This allowed easy identification of who was speaking in the final transcribed word processing document. This process was followed for all thirteen interviews.
Following transcription, the word processing documents were analysed using the computer program HyperRESEARCH (Version 2.8). HyperRESEARCH is a computer program used to analyse and highlight words, sentences and phrases from transcription and categorise them (Hesse-Biber et al. 1991). HyperRESEARCH allowed for themes to be coded and aggregated so that reports could be made for each of them. For example, if a participants‟ discussion included the comment “I trust the winery”, this section of the transcript would be coded as “trust” and similar discussion would also be coded as such. Following coding of each IDI, a report was made of all the coded discussion, allowing the researcher to see all the discussion regarding each code.
3.7 Exploratory study results The results from the exploratory phase of the study were coded and analysed in the HyperRESEARCH computer software program. As previously mentioned, the software allowed reports to be produced, including a report on the frequency of codes. Table 3.2 46 illustrates the frequency of discussion of topics in the IDIs. The purpose of the table is to illustrate the level of discussion on each topic and, how it related to the research objectives discussed in 3.5.
Table 3.2: Frequency of topic (code) discussion in in-depth interviews
Topic of discussion Frequency of comment
( number of times)
Communication 62
Trust 38
Satisfaction 22
Power asymmetry 16
Winery issues 15
Discussion about preceding vintage 8 (grape harvest)
The table illustrates that topics related to the relational norm of communication had the highest level of discussion, with discussion regarding relationship quality dimensions (i.e. trust and satisfaction) accounting for the second and third highest topics of discussion. However, the specific comments that were made by participants must be viewed in terms of the research objectives detailed in section 3.5. The specific comments, as they relate to the research objectives, are outlined in the next section.
3.7.1 Research results related to uncovering the effect that collaborative communication theory has on relationship quality As illustrated in section 3.7 the relational norm of communication was of crucial importance to grape growers, evident in their frequency of discussion in Table 3.2. The research results affirm the literature (Morgan & Hunt, 1994; Mohr & Nevin, 1990; Mohr, et al. 1996) which has commented that communication positively influences the buyer-supplier relationship. Some representative comments (i.e. representative of similar comments by other participants) include the following:
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Participant 6:
“ I think that communication is without and in this scenario (in the current relationship with their winery) and it is the most valuable thing you have got in the relationship” Participant 1:
“ I just like good honest communication……I know times have been hard and wineries need to make cutbacks but good honest communication is what is needed”
Participant 11:
“One guy rejected our fruit because he said it had too much MOG (material other than grape) in the bins……I reckon he just didn’t have the space to take the fruit…..I would have felt better if he’d been honest....I would have trusted him more”
These comments affirm the notion that the honesty and completeness of information aid the relationship, and therefore enhance relationship quality. Of interest was the discussion relating to communication‟s influence on trust and, therefore, relationship quality. A representative comment included:
Participant 9:
“ We just entered into a 5 year contract with these guys and it is fabulous…..it’s a small company and the GM (General Manager) popped around the other morning for breakfast…..it was great to be able to talk with him…I have a good feeling about these guys and I really trust them to do what is best for me”
This comment relates to the concept of trust and that communication positively influences trust, which is determined as a measurement of relationship quality.
Participant 2:
“ They had the winemaker come over……then the viticulturalist……then the grower liaison…..they all seemed to be saying different things………confused the hell out of me…I don’t know how much I trust these guys are all telling the truth”
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Daft & Lengel (1984), comment that certain modes of communication provide richer, more complete information. Therefore, it was of interest to observe, in the causal stage of the study, how specific modes of communication influence relationship quality.
As a result, comments regarding communication modality were linked to the creation of contract and further linked to trust. Such a representative comment included the following:
Participant 4:
“ The last guys that set up the contract were great…..they just came to the house (the house of the grape grower) and we discussed it and we liked it so we signed……when it finished (the contract) we changed to a different winery….they just emailed us their terms and asked us for our terms….would have been better if they just came and talked to us”
Participant 7:“ Would’ve been better to work out the contract face to face than over the phone or the fax”
These comments are linked to the nature of the contract creation and allude to the notion that face to face communication, as opposed to electronic computer modes, created more trust in the winery and more satisfaction. This is also links to Daft and Lengel‟s (1984) discussion that rich modes of communication (i.e. face to face) are better than less rich modes. The comments are also linked to the formality of communication as proposed by Mohr & Nevin (1990) and Mohr et al. (1996) where written modes of communication create more trust as opposed to word of mouth modes of communication. It appears that these comments from growers seem opposed to the views expressed in the literature. Thus, it can be surmised that formal communication decreased trust and satisfaction.
Further comments were made by respondents with respect to the bi-directionality of communication. These comments included:
Participant 11:
“feedback from the winery was good”
Participant 6:
“winery talked to us a lot…..but didn’t do much listening…..they weren’t interested in what we had to say” 49
Participant 10:
“they (winery) did all the talking…….rarely listened to what I had to say…..it didn’t like this….made me feel like what I had to say didn’t mean anything”
Participant 3:
“ they (winery) never cared about what we said….i didn’t trust them…..yeah that didn’t make me feel good”
Participant 7:
“We never talked to the winery…….they told us what they wanted and we gave them the grapes…..i didn’t really care as long as I got paid”
Participant 12:
“Just gave us MOG and brix and other measurements………didn’t say much until picking….didn’t bother me too much”
Participant 10:
“gave us the specs (grape specifications) and we did the spray diary (which catalogues the spraying of chemical for export requirement) and that was it…..didn’t ask them much
Participant 1:
“winery talked a lot…..we only contacted them a few times…..it did feel good….them checking up on us’
These comments allude to the fact that the winery was producing much of the communication. While respondents were given information regarding grape specifications and the use of spray diaries to record the spraying of chemicals for wine export requirement, the respondents‟ communication input appeared to be minor. It can therefore be surmised from the comments that the communication in the relationship was almost exclusively being transmitted from the winery and that bi-directionality of communication was not evident. In addition to this, there was no decrease in trust or satisfaction from respondents. Therefore, the uni-directional communication from the winery positively influenced trust and satisfaction
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Proposed by Mohr & Nevin (1990) is the concept of non-coercive communication attempts. This concept is based on the premise that communication can indirectly make an actor take a course of action, without being directly asked to do so. It can be surmised that the characteristics (for example, demeanour, wit or charm) of the actor transmitting the information can make another actor take action without specifically being asked to do so. A representative comment by a respondent alluded to this notion:
Participant 3:
“…..he’s (the winery representative) a big, imposing guy whom I’ve never trusted…I didn’t want to piss him off…..he didn’t ask us to complete the survey (a survey regarding the vineyard details)…but I did I because I didn’t want to piss him off….I didn’t want to do it otherwise”
This comment alludes to the notion of non-coercive communication attempts whereby this participant performed a task, without specifically being asked, because of wanting to please the winery representative (a person that was not trusted); however, it appears that the action did not create satisfaction. Non-coercive communication attempts are an effect of communication whereby without an explicit instruction to an actor, the actor obeys by the communication transmitter‟s wishes due to factors such as intimiation, reputation and body language affets (Mohr & Nevin, 1990). In term of the respond‟s comments, it can be concluded that the non-coercive communication attempts negatively influenced trust and satisfaction.
Much information that was gleaned from the discussion related to relational norms that affect the grape growers‟ perspective of the relationship. Many of the comments were centred on communication and how its various aspects affected trust and satisfaction. However, discussion also occurred regarding how industry issues were affecting participants‟ perceptions of the relationship.
Many comments were made by respondents that the wine industry was suffering economic hardship. The hardship manifests itself in many ways, particularly in the use of power. Such comments included the following:
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Participant 2:
“We know times are tough…..we were around in the 80s (difficult period) but they (winery) shouldn’t treat us as though we are stupid……I really don’t like it”
Participant 3:
“There are too many companies (wineries) just squeezing us too hard…..it’s difficult (the current industry scenario) but they could be a little more honest….now I don’t trust them as much”
Participant 10
“ the wineries sometimes take advantage of the fact that we have no alternative market for our grapes…also because of oversupply of grapes..”
Participant 11
“ there are often threats of rejection of our grapes “
These comments illustrate that participants have knowledge of issues related to industry oversupply and they believe that some wineries were exploiting the oversupply of grapes scenario to better suit their circumstances. This may be a result of a power asymmetry in the relationship which favours the winery, and this coercive power is leading to decreased trust as proposed by Morgan & Hunt‟s (1994) extended KMV model of relationship marketing. Furthermore, the climatic conditions that lead to power asymmetry are evident in their assessment of grape quality and lead to the rejection of the grapes. This action highlights the notion that wineries have the greater power in the relationship and wish to take whatever action is necessary to maintain it, as discussed by Cox et al. (2001). This scenario leads to conflict and disturbance, as discussed by Gaski (1984) and Seyed- Mohammed & Wilson (1990). It can be surmised that this power imbalance, and the resulting conflict, diminished relationship quality. Specific comments were specifically made that the coercive power of wineries was diminishing the level of trust and satisfaction in the relationship. This concept is evident in comments whereby the participant mentioned that “now I don‟t trust them as much” and “I really don‟t like it”. In the light of these comments, it can be surmised that power is negatively influencing trust and satisfaction.
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3.8 Exploratory research findings and relevance to literature The exploratory research results have uncovered numerous dimensions of relational norms and relationship quality between grape growers and wineries. The aim of the exploratory research study was to provide a result which, in view of the literature, would allow for the creation of a conceptual model for testing via quantitative methods in the causal stage of the study. Therefore, a discussion of the results and the literature follows.
3.8.1 Research results on communication modality and relevance to literature and hypothesis development Discussion in the literature regarding communication modality suggests that face-to- face forms of communication positively influence satisfaction (Daft & Lengel, 1984). Mohr & Nevin (1990) and Mohr et al. (1996) further discuss frequency, which is manifest in modality, as influencing satisfaction; however, Mohr & Nevin (1990) do not distinguish between the modalities of communication and frequency. The results of the exploratory study suggest that face-to-face or direct modes of communication positively influence trust and satisfaction, while non face-to-face (or indirect) modes decrease trust and satisfaction. However, the results do not distinguish whether they only influence trust or satisfaction and therefore, relationship quality. Thus, in light of the results and the literature, the following hypotheses were formulated:
H1. Face to face (direct) modes of communication positively influence trust
H2. Face to face (direct) modes of communication positively influence satisfaction
H3. Non Face to face (non direct) modes of communication negatively influence trust
H4. Non Face to face (non direct) modes of communication negatively influence satisfaction
3.8.2 Research results on communication directionality and relevance to literature and hypothesis development The literature defines communication as bi-directional; thus communication flows in both directions i.e. from buyer to supplier and from supplier to buyer (Mohr & Nevin
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1990; Mohr et al. 1996). Mohr & Nevin (1990) comment that bi-directionality does influence satisfaction but did not test the effect of directionality on satisfaction. The exploratory research results of this study suggest that bi-directionality of communication is minimal in the relationship and is uni-directional from the source of the buyer (winery). The results do suggest that the uni-directional communication does positively influence participants‟ trust and satisfaction in the relationship and therefore, relationship quality. In view of the literature and the research results, the following hypotheses are posited:
H5. Uni-directional communication (feedback) from the winery positively influences trust.
H6. Uni-directional communication (feedback) from the winery positively influences satisfaction.
3.8.3 Research results on non-coercive communication attempts and relevance to literature and hypothesis development Non-coercive communication attempts is an element of collaborative communication as posited by Mohr & Nevin (1990). Mohr & Nevin (1990) discuss how it affects the relationship, but did not observe how the dimension affects trust or satisfaction and merely combined the notion with other elements of collaborative communication in a summated scale. The results of the exploratory study suggest that non-coercive communication attempts negatively influence trust and satisfaction and as a result, relationship quality. Therefore, in view of the literature and the research results, the following hypotheses are posited:
H7. Non-coercive communication attempts from the winery negatively influence trust
H8. Non-coercive communication attempts from the winery negatively influence satisfaction.
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3.8.4 Research results on communication formality and relevance to literature and hypothesis development Mohr & Nevin (1990) discuss the concept that formality of communication aids the relational partner in clearly defining and understanding what is expected in the relationship. While not directly testing the effect of formality of communication on trust and satisfaction, Mohr et al. (1996) do comment that it has a positive effect on satisfaction but do not comment on its effect on trust. The result of the exploratory study suggests that formality negatively influences trust and satisfaction, which is in conflict with the discussions of Mohr & Nevin (1990) and Mohr et al. (1996). Therefore in view of the literature and the research results, and particularly in light of the discussion above where communication from the winery seems uni-directional, the following hypotheses are posited.
H9. Formality of communication from wineries negatively influences trust
H10. Formality of communication from wineries negatively influences satisfaction
3.8.5 Research results on power asymmetry and relevance to literature and hypothesis development The literature suggests that power asymmetry affects the relationship and creates disturbances and conflict, and decreases the level of trust and satisfaction in the relationship (see Cox et al. 2003, Gaski, 1984, Seyed Mohammed & Wilson, 1990). The results of the exploratory study suggest that a strong power asymmetry (favouring the winery) exists in the Australian wine industry. The results illustrate that this power asymmetry affects the level of trust and satisfaction in the relationship. Therefore, in view of the literature and these results, the following hypotheses are posited:
H11. A power asymmetry favouring the winery is decreasing grape growers‟ perception of trust in the relationship.
H12. A power asymmetry favouring the winery is decreasing grape growers‟ perception of satisfaction in the relationship.
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3.8.6 Relationship quality and relevance to research results The literature on relationship quality does not define a clear measure of the construct. For example, Crosby et al. (1990), Wray et al. (1994), Kim & Cha (2002) and Kim et al. (2006) for instance, operationalised the relationship quality construct as indicative of the level of satisfaction. Others such as Leuthesser (1997), Dorch et al. (1998), Naudé & Buttle (2000) and Parsons (2002) discuss relationship quality‟s relevance to trust, satisfaction, commitment, opportunism and customer satisfaction. The framework proposed for this study defined relationship quality as a measure of trust and satisfaction; however, the literature does suggest that satisfaction positively enhances trust (Mackenzie & Hardy, 1996) with Geyskens et al. (1999) arguing that if the channel members are highly satisfied, the partners believe them to be more trustworthy and Batt (2003, p 69) stating that “…satisfaction with an exchange will lead to some initial trusting behaviours, but as satisfaction increases, trust will increase”. The literature does suggest that satisfaction positively influences trust, but no concrete link was found in the exploratory study linking trust and satisfaction. However, the following comment was made by one respondent:
“they (winery) never cared about what we said…I didn’t trust them…..yeah that didn’t make me feel good”
This comment seems to suggest that trust leads to a sense of feeling good, or satisfaction. However, this link between the two constructs was not evident in other participants‟ discussions. The results and the hypotheses formulated suggest that trust and satisfaction exist in the relationship (and are influenced by the various communication elements and power) and therefore allow for an observation of relationship quality, but there appears to be no link between them. In view of the exploratory study results, no link between trust and satisfaction can be said to exist.
3.9 Exploratory study research objectives overview The exploratory study had two research objectives. These were:
1. to uncover the extent to which Mohr & Nevin's (1990) collaborative communication elements affects wine grape growers' perceptions of relationship quality; and
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2. to identify the extent to which power asymmetry is affecting grape growers‟ perceptions of relationship quality.
In relation to the first of these, it was found that collaborative communication affects trust and satisfaction and therefore relationship quality. In relation to the second of these, it was uncovered that power asymmetry in the relationship, favouring wineries, affects growers‟ perceptions of relationship quality.
3.10 Limitations of the exploratory study The exploratory study provided information regarding the relationship that grape growers have with wineries. The information was used to validate a theoretical model (Figure 3.1) of grape grower perceptions of relationship quality in the Australian wine industry. However, the exploratory study has a key limitation. The participants‟ businesses were located in South Australia and Victoria and, while these states comprise the major grape growing areas of Australia, other states in Australia contain other grape growing areas that were not represented by participants for the exploratory study sample. Furthermore, participants were located in only five different wine regions and 13 grape growers participated in the study, which is a relatively small sample (Malhotra et al, 2006). However, the size of production and quality of production of the participants in the exploratory study do allow for some generalisations to the Australian grape growing industry.
Furthermore, this thesis has employed a mixed method approach, and as the exploratory phase of the study is smaller in size (number of participants and scope of analysis) than the causal and descriptive stage, this research stage is justified in terms of size, unlike a triangulation study where both quantitative and qualitative methods are similar or equal in size (Cavana et al, 2001; Cresswell, 1994). Similar studies in these areas of research have also employed similar participant sizes in the qualitative phases (Hobley, 2007; Plewa, 2008).
3.11 Hypothesised model The preceding literature and research results have provided many hypotheses for examination in the causal stage of the study. These hypotheses are combined graphically into a model which is shown in Figure 3.1 57
Figure 3.1: Conceptual model of grape grower perceptions of relationship quality in the Australian wine industry
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3.12 Alternative model In Chapter 2 it was shown that relationship quality was measured as a multi- dimensional, higher order construct consisting of trust and satisfaction. Authors such as Crosby et al. (1990), Dorch et al. (1997), Kim & Cha (2002) and Kim et al. (2006) empirically tested relationship quality, mostly via SEM and other multi-variate regression techniques, using trust and satisfaction as separate constructs, and they discuss whether higher levels of trust and satisfaction in the model correspond with higher levels of relationship quality. This proposition has been used as the basis of the exploratory study, as participants were asked how they perceived the various dimensions of collaborative communication and power asymmetry based on trust and satisfaction.
However, Scheer & Stern (1992) and Leuthesser (1997) empirically tested relationship quality as a uni-dimensional construct whereby the construct of relationship quality consists of latent variables of trust and satisfaction. SEM literature discusses whether this alternative (or 2 step model estimation) can be performed in order to observe which model best fits the data concerned (Joreskog & World, 1982; Anderson, & Gerbing, 1988; McDonald & Ho, 2002). In this instance, it would be of interest to observe a model which estimated relationship quality as a uni-dimensional construct as opposed to a multi-dimensional one, thereby satisfying a theoretical and methodological concern.
As such, the constructs exhibited in Figure 3.1 would directly affect relationship quality in the alternative model as opposed to the multi-dimensional effect shown in Figure 3.1. The hypotheses would remain the same, although each independent variable in the model (i.e. power, collaborative communication elements) would affect the singular dependent variable (i.e. relationship quality). Furthermore, the results of the exploratory study showed that each element of collaborative communication and power had the same effect on trust and satisfaction and would therefore affect relationship quality the same as the uni-dimensional construct consists of the two factors. For example, power was shown to negatively affect trust and negatively affect satisfaction in the literature review and in the exploratory study. Therefore, in the alternative model, power would negatively affect relationship quality, as relationship quality consists of trust and satisfaction. Thus the alternative model hypotheses would be:
H1a. Face to face (direct) modes of communication positively influence relationship quality. 59
H2a. Non face to face (non direct) modes of communication negatively influence relationship quality.
H3a. Uni-directional communication (feedback) from the winery positively influences relationship quality.
H4a. Non-coercive communication attempts from the winery negatively influence relationship quality.
H5a. Formality of communication from wineries negatively influences relationship quality.
H6a. A power asymmetry favouring the winery decreases grape growers‟ perception relationship quality.
Figure 3.2 graphically illustrates the alternative model.
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Figure 3.2 Alternative model based on uni-dimensional definition of relationship quality and grape grower perception of collaborative communication and power asymmetry
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3.13 Chapter conclusion This chapter has discussed the exploratory study, including the qualitative study methodology, the findings and hypothesis development, and has concluded with a conceptual model derived from the hypotheses. The next chapter will discuss the descriptive and causal research methodology, which will be used to test the conceptual model and its various hypotheses.
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Chapter 4: Descriptive and Causal Research Methodology
4.1 Chapter outline This chapter outlines the methodology employed in the descriptive and causal research stages of the study. The chapter begins with a discussion of how the data was collected during these research stages, and the techniques used to analyse the resulting data.
The chapter summarises the scale item measures used in the descriptive and causal research stage and gives a discussion on the source of the scale items. The statistical procedures used to analyse the data are presented, and the chapter concludes with a summary of the methodology.
4.2 Quantitative research methodology design The research hypotheses and conceptual model that were devised in Chapter 3 are tested by the methodology outlined in this chapter. This study employed a positivist epistemological perspective whereby a scientific, validity approach was used to test the hypotheses and the model devised in Chapter 3 (Wacquant, 1992; Cohen & Maldonado, 2007). To gain the descriptive and causal results, structured equation modelling was used to test the model and thereby confirm the hypotheses (Hair et al., 2006). As such, a quantitative research method was employed.
A survey was used to acquire the descriptive and causal information from the sample population. The survey method was an appropriate means to collect the large numbers of responses required for hypothesis testing, is simple to administer, and relatively undemanding for the respondents to complete (Malhotra et al., 2006; Hair et al., 2006). The survey instrument consisted of a structured questionnaire with questions placed in a predetermined order. The questions posed to the respondents were, in the main, quantitative in nature and were devised to gain the information required to test the hypotheses in the causal stage of the study, but also to validate the study through descriptive statistics (discussed in Chapter 5) (Malhotra et al., 2006).
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4.3 Data collection method Preceding the creation of the questionnaire instrument, a large amount of time was invested in examining the academic and wine industry trade literature and the exploratory research results to ensure that the developed scale item measures were suitable to measure what was required in the descriptive and causal stages of the study. The constructs (i.e. collaborative communication elements, power and trust and satisfaction) depicted in Figure 3.1 were operationalised in the questionnaire using multiple measures that had been utilised in previous studies.
The scale items in the survey were modified numerous times to improve the efficacy and content of the questions used. This process went for five rounds so that each questionnaire item was clear and easy to understand by the intended respondent. The questionnaire was pilot tested on 15 respondents to gain insight into whether the respondents understood the questions and could successfully complete the questionnaire. The small number of pilot test respondents was due to the sample population size (4500- 8000 grape growers in Australia), and as pilot study respondents were precluded from the main data collection phase for validity reasons, a large pilot study response would have restricted the number of potential respondents in the final sample.
On completion of the questionnaire, the study investigator met with the pilot test respondents and discussed each questionnaire item, asking if they understood what the question was asking of them (i.e. was it easy to understand) and querying if the question could be posed a different way. The questionnaire contained 63 questions which gave a pilot study respondent ratio to scale items of 4.2: 1 which is considered acceptable according to Cavana et al., (2001). In addition, the questionnaire was examined by wine industry professionals, including heads of grape grower associations and wine industry experts, to gain their opinions of the efficacy of the scale items and the overall effectiveness of the questionnaire. Each of the wine industry experts examined the questionnaire and, on completion, was queried as to whether the questions were appropriate for the intended sample frame (i.e. would the questions be understandable to grape growers) and if any questions should be discarded or new questions devised. This second stage was of critical importance as it improved the first section of the questionnaire related to specific questions about grape contracts such as price per tonne, respondents‟ vineyard acreage, and overall crop price. The wine 64 industry professionals generally commented that the contents of the questionnaire were sound.
4.3.1 Quantitative study sampling procedure and sample size The survey population for the quantitative research study were contracted grape growers. These were independent wine grape growers currently supplying wineries; only wine grape growers who supplied wineries with grapes, as opposed to making their own wine, were eligible to complete the questionnaire. In consultation with wine industry experts, it was deemed appropriate to survey non-wine making grape growers because including those that make and market wine may give distorted results. They (wine making grape growers) would be in the business of making wine; as such they may contract other grape growers to obtain grapes, and this may bias some of their opinions regarding wineries and may affect their questionnaire results.
The survey population was from all states in Australia where wine grapes are grown and included Western Australia, South Australia, Victoria, Tasmania, New South Wales and Queensland and the survey was administered from March to July 2009. Separately from the data collected to test hypotheses and the conceptual models, the survey was also designed to obtain information regarding the business and the demographic characteristics of respondents, and this was used to cluster respondents by their responses (Malhotra et al., 2006; Hair et al., 2006).
The survey population included independent wine grape growers who could be classified according to the varying natures of their business structures. The respondents‟ business structures included large investor-owned vineyards, managed investment schemes, small part time producers, and long term, grape growing families. Therefore, the business structure falls in line with the grape grower classifications of PIRSA (Primary and Resources South Australia) wine divisions (PIRSA, 2006).
The census, and therefore the size of volume grape growers in Australia was also determined and played a part in determining the representativeness of the primary study respondents in relation to the target population. However, statistics on the number of grape growers in Australia are not accurate. The Australian Bureau of Statistics (ABS) (2005) and Hobley (2007) reported that 8,347 individual grape growing establishments exist in Australia for the purpose of winemaking, drying and fresh fruit consumption. A breakdown of establishments that specifically grow grapes for wine making was not 65 available; however, Hobley (2007) reported that 90% of the grape growing establishments grow grapes for the production of wine. Furthermore, the study sample frame included independent wine grape growers who supplied wineries and the ABS figures do not discriminate between independent grape growers and wineries that grow grapes for their own wine production. Further investigation by the author revealed that the recent industry economic downturn had reduced the number of establishments and that the number of grape growers in the sample frame may be as low as 4500 (Mckenzie pers. comm., 2009).
The wine grape industry does not have a database of contact information for the sample population and thus wine industry bodies such as wine grape grower associations and private companies that have contact with grape growers were used to obtain grape grower information. Therefore, by necessity the descriptive and causal stages of the study (relying on quantitative data) had to rely on a non-representative sample. However, the descriptive and causal research studies wished to achieve representativeness of the wine grape growers in terms of the size and geographical location of the businesses, particularly in terms of the state where production was made.
Wine grape grower associations and private companies were willing to provide assistance in terms of giving direct access to their grape growers via electronic distribution of the questionnaire. The wine grape grower associations (e.g. in the Murray Valley, Riverina, Barossa, McLaren Vale, Adelaide Hills, Tasmania, King Valley, Granite Belt and Hunter Valley) assisted by electronically distributing the survey to their constituents and provided comments of endorsement. Private companies (including grower liaison companies and large wineries) also provided access to their growers using a similar method, including wine industry news services. Assistance from the associations and companies provided a good regional, state and production (quality of grape production focus) representation in the final sample. The representativeness of the final sample is discussed in Chapter 5. The survey was completed in less than four months.
A large number of respondents was desirable due to the large number of relational variables devised in the conceptual model and the use of multivariate statistics such as structural equation modelling (Hair et al., 2006). In general, the number of respondents required depended on numerous factors such as:
the level of precision of results (confidence interval);
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the acceptable risk in predicting the level of precision;
time and cost constraints;
size of the actual population; and
variability in the population.
(Ticehurst & Veal, 2000; Cavana et al. 2001; Malhotra et al. 2006)
4.3.2 Administration of survey instrument Two methods were used for the administration of the survey instrument to grape growers. The main survey methodology was via online administration. The survey was uploaded onto an online survey administration portal which allowed the respondents to complete the survey via an internet web browser. The web administration of the survey instrument was deemed an efficient and cost effective way of accessing respondents due to the geographically disparate nature of respondents‟ places of residence and the cost issues related to paper administration of the survey where paper surveys are delivered to the respondents and then self-completed and returned. The online methods reduced the amount of postage and paper expense that would normally be associated with paper administration. Respondents were also able to complete the questionnaire at their own pace and convenience and were able to save their responses online for later completion.
The two methods of administration were as follows:
1. Firstly, the grape grower associations and private grower liaison companies were sent a web URL link to the web site of the survey. The associations and companies then sent a group email to the grape growers on their databases and the grape growers were then able to complete the survey.
2. Secondly, the details of the web URL and a description of the study were posted on the web site of grower liaison companies and on the web site of various Australian wine industry news web sites, frequently viewed by grape growers.
A prize of $2000 of viticultural services was offered to respondents to motivate them to respond. This was deemed necessary to increase the response rate due to the lengthy
67 nature of the survey and due to the prevalence of survey fatigue in the Australian wine industry, as it is widely surveyed.
This type of approach was deemed appropriate by similar studies in the Australian wine industry (Boyce & Neale, 2006; Hobley, 2007).
Table 4.1 illustrates the grape grower associations and private organisations that provided access to, and assistance in, obtaining responses. This table indicates that grape grower associations from all wine grape growing states (i.e. Tasmania, South Australia, Victoria, New South Wales, Queensland) assisted in administering the survey and therefore in making responses from all states achievable
Table 4.1: Grape grower associations and private organisations that provided access to respondents
Grape grower associations Private companies Adelaide Hills Wine Region Inc. Morton Blacketer
Coonawarra Vignerons Association Davidson Viticulture
Goulburn District Vignerons Association Constellation Wines Australia
Hunter Valley Wine Industry Association Orlando Wyndham
King Valley Vignerons Fosters Wine Estates
Barossa Grape and Wine Association Wine Biz Online
Wine Industry Tasmania Australian Grape Grower and Winemaker
Great Southern Wine Producers Association
Granite Belt Wine Growers Association
Swan Valley & Regional Winemakers' Association Inc. McLaren Vale Grape, Wine & Tourism
Murray Valley Winegrape Growers Association
Riverina Wine Grape Marketing Board
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While a non-probability sample existed for the study, efforts were taken to reduce the level of self-selection bias associated with web-based surveys (Zikmund & Babin, 2007) by observing whether the respondents matched the sample frame. Associated with the $2000 prize, respondents had to enter their personal business details (name of person completing the survey, telephone number, business address). A random sample of 30 respondents were contacted from the list and asked whether they had completed the survey. In all 30 cases, the respondents matched the characteristics of the sample population thereby allaying the problems associated with self-selection bias and false representation.
4.3.3 Questionnaire design Numerous issues were considered when devising the design of the questionnaire. The most important factors were, as discussed by Cavana et al., (2001), the research objectives, the sample size, the method of distribution, the sample frame, the data input method and the type of analysis. The questionnaire contained two types of questions. Unstructured questions, which were open-ended in nature, were mainly used to gain information regarding the respondents‟ business details; structured, specific response questions were used mainly in the form of multiple choice and scaled questionnaire items.
The questionnaire used two types of scales. Firstly nominal scales were used to describe the differences in a characteristic of the respondent, for example, 1= small winery contracted, and 2= medium winery contracted. However the majority of scales used were interval in nature; this was required for the multivariate analysis (Hair et al., 2006). In the interval scale questions respondents were asked to indicate on a seven point Likert scale their agreement or disagreement with a statement. A seven point Likert scale was used in the majority of the scale items that were adapted for this study because it was important to maintain consistency (Hair et al., 2006).
The questionnaire was divided into three sections. The survey commenced with a brief introduction to the survey, explaining who was eligible to complete the survey, and an outline of the prize incentive.
The questionnaire asked the respondents to focus on the most important relationship they had with a winery when answering the questionnaire items. This was directed in consultation with wine industry experts because respondents may have had numerous 69 relationships with different wineries and it was not deemed appropriate for them to answer the questionnaire items for each relationship as that would have taken a great deal of time to complete and cause fatigue (Hair et al., 2006). For example, a respondent may have their grapes contracted to three wineries and it would have been an onerous task for them to complete three questionnaires, one for each relationship, so they completed one questionnaire focusing on their most important relationship. The ramifications of this are discussed further in Chapter 6 and Chapter 7.
Section 1 contained questions where growers had to discuss the business details of the contract they had with a winery. These questions included the length of the contract with the winery, how many tonnes of grapes were supplied, the dollar amount of the grapes supplied, the price per tonne of the grapes, and whether the respondent supplied any other wineries. The questions in Section 1 allowed for the comparison of responses based on the contracting relationship that existed between the respondent and a winery. The responses also allowed for variables that could be used for clustering purposes. Section 2 contained the bulk of the questions regarding the research hypotheses and objectives. Section 3 was designed to gain information relating to the details of the respondent‟s business. This included questions regarding the size (in acres) of the vineyards of the respondent, the years the respondent had been producing grapes and been in the grape growing business, the number of people who worked for the respondent‟s business, the wine region the respondent‟s business was in, whether the respondent was contracted to a winery in terms of the winery size (small, medium or large), and the ownership of the winery (publicly or privately owned). As in Section 1, Section 3 responses could be used as clustering variables for later analysis. The questions in Section 3 could also be used to observe the location, size and general business “demographics” of the respondents.
4.3.4 Modification of questionnaire to online format A vast amount of time and effort was devoted to modifying the questionnaire into the online format. While the efficacy and validity of the questionnaire items was tested in a paper format (via internal modification and testing on a pilot sample of grape growers and wine industry experts), the online modification was a further process that was necessary in order for the instrument to be easy to complete and understandable by the sample population.
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An online survey provider was hired to host the questionnaire. The service they provided included hosting the web pages that contained the questionnaire and providing mechanisms for collating the data and downloading it into data analysis software. The provider also had mechanisms to ensure data protection and minimise fraud. The questionnaire was uploaded, in an electronic form, into the provider‟s web site. From there it was modified to be aesthetically pleasing and easy to read. The questionnaire was aesthetically modified via html to change the appearance and size of words, by making them bold or underlining them, or by increasing or decreasing font sizes in the questionnaire items. The Likert scales were also modified to highlight terms (for example, AGREE) and to fit the scale into a web page. This process was performed to make the items easier to read.
When modifying questionnaire items and the scale to fit into a computer screen, consideration was given to the size and resolution of the screen. Time and effort was spent on this issue as it was deemed important that survey response errors, such as false or non-responses, be minimised (Ritter & Sue, 2007). For example, if a respondent had a computer with a large screen (e.g. 21 inches in diameter) with a high resolution (e.g. 800-1000 horizontal pixels), the words on the screen would be in a very small font and the Likert scale would be long on the screen. Conversely a respondent with a small screen and a small resolution (12 inches in diameter and 400-600 horizontal pixels) would view the questionnaire in a large font size and the Likert scale would fall off the screen requiring the respondent to scroll across to fill in the scale; this would have created respondent fatigue and possibly created inaccurate results (Ritter & Sue, 2007; Zikmund & Babin, 2007).
After consultation with an IT expert (Matthews pers. comm., February 2009), it was found that most respondents would have a screen approximately 14-17 inches in diameter with a 600-800 horizontal resolution .Therefore, the font size of questionnaire items and scale length was modified with these parameters in mind so that the font was large enough to read and the scale did not require scrolling across the screen to complete.
The online questionnaire was divided into six html web pages so that questionnaire items and scales could be displayed properly, in a vertical fashion. The respondents did not need to scale the screen vertically to a great degree. Utilising six pages allowed the respondent to avoid becoming too fatigued by replying to questions with too many items on one html page. After completing each page, the respondent clicked a button (at 71 the bottom of the page) and was directed to the next html, and so on, until all the pages were completed.
After all aesthetic modifications were completed, the online questionnaire was further pilot tested on five grape growers who were then met by the investigator. As in the pilot testing of the initial phase of the questionnaire, a small number of pilot testers were used so as not to exclude a large number of potential respondents from the final questionnaire response. The investigator questioned the respondents to gauge whether they believed the layout of the questions was appropriate and easy to understand, and whether the size and style of the questionnaire items and scale was appropriate for their computer screen.
After this process was completed, the questionnaire was ready for deployment to the sample population. A copy of the questionnaire is shown in Appendix 1. This copy is a replication of the online version in a paper form, and as such, the representation is not identical as certain elements of the online format (drop down menus, borders) cannot be reproduced on paper. However, its question and scale content is identical.
4.3.5 Protection of questionnaire information against online fraud Time and effort were taken to mitigate against the effects of online fraud. The main concern was mitigating against accidental multiple responses and the hacking (reprogramming of the questionnaire or questionnaire responses for fraud reasons), particularly in relation to false responses to gain further entries into the questionnaire incentive (Wright, 2005). The protection of the questionnaire and respondent information from fraud was performed in two ways.
Firstly, the online survey provider had an IP (internet protocol) address registration system. All internet enabled computers have an IP address and the provider logged each IP address of the respondents who completed the questionnaire. This allowed respondents to finish completing the questionnaire at a later date if they did not fully complete it in one attempt by returning to the question they last completed. The IP logging also allowed the rejecting of respondents if they had already completed the survey. If an attempt to complete the survey a second time from the same computer was made, the respondent was greeted with a message stating they had already completed the questionnaire and was denied further access to it. To combat the issue that respondents could complete the questionnaire at an additional time using another 72 computer, which therefore had a different IP address, respondents were asked to give their contact details to win the prize; therefore, it was easy to observe if they had completed the questionnaire a second time, and all responses that did not contain contact details were rejected from the final valid response set. These measures were deemed appropriate to mitigate against such issues (Rolland & Prakash, 2005; Wright, 2005).
Secondly, to further combat fraud, the responses were manually screened by the investigator to observe if any responses were too similar or contained information that was irregular or blatantly incorrect (for example, an irregular response might state that they had received $72,000 per tonne for their grapes, which is blatantly not possible). All suspicious responses were deleted from the final valid set of responses. This technique aided in combating “hacking” fraud by online miscreants.
This thorough process revealed that no intentional fraud occurred and, in all, 48 responses were deleted from the final valid response set due to irregular or blatantly wrong responses, no contact details being given, or due to suspicious responses, leaving 396 valid responses. No major fraud or hacking was encountered in the online survey process. It could be reasoned that all rejected responses were due to mistakes and confusion rather than wilful fraud.
4.3.6 Section 2: Scale items relating to research hypotheses The focuses of the scale items in the questionnaire were to test the research objectives and hypotheses. Section 2 of the questionnaire contained all the questions relating to the research objectives and hypotheses.
The first questions in Section 2, regarding the frequency and mode of communication, are show in Figure 4.1.
Figure 4.1: Questionnaire scale items regarding the mode of communication
For each of the following methods, over the 2009 Vintage growing season (August 08- May 09), please estimate the frequency (the number of times) with which the winery communicates with you via these various methods.
Please type in the "number of times" as a number, e.g. "4" rather than "four". If you did not communicate via a certain method, please put "0" 73
Face to face interaction with winery people (number of times) (Required)
Telephone interaction (telephone calls) with winery people (number of times) (Required)
Written letters and all written correspondence (non-electronic e.g. no email) (number of times) (Required)
Direct Email, from a winery representative to you (number of times) (Required)
Seminars [e.g. Grower Days (winery - growers meetings)] (number of times) (Required)
General newsletters from the winery (number of times) (Required)
Other (number of times)
The instructions accompanying the questions and the nature of the modalities of communication were gleaned from scale items obtained from Mohr et al., (1996) and adapted from Cannon & Homburg (2001). The specific modalities (e.g. computer, seminars, etc.) were added after consultation with Australian wine industry experts as the modalities needed to be relevant to the industry. Further scale items from Prahinski & Fan (2007), Kwon & Suh (2004), Claycomb & Frankwick (2004), Morgan & Hunt (1994) Redondo & Fierro (2005), Petersen et al., (2005), Lusch & Brown (1996) and Heide & John (1992) were used as comparison scale items, mainly to gain examples of the wording of questions in relation to communication. Formality of communication was the topic of the next set of questions designed to test the research hypotheses. The questions were as follows:
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Table 4.2: Questionnaire scale times regarding the formality of communication Please indicate how strongly you agree on the following statements When working with this winery, formal communication channels are followed (i.e. communication is formal, regular and structured) versus casual informal, word –of- mouth modes). The terms of our business contract with the winery have been written down in detail. The winery‟s expectations of us are communicated in detail. The terms of our business relationship with the winery have been explicitly put into words and discussed. Information sharing on important issues has become crucial to maintaining this partnership. We share a common, specialised IT software system dedicated to facilitate communication with the winery (e.g. Vine Access®). Grower liaison committees, that communicate my issues and concerns with the large wineries, are effective.
These questions are based on the Mohr and Nevin (1990) collaborative communication elements. They were derived from that study and the Mohr et al.,(1996) study and wording was adjusted to be relevant to the wine industry, and done in consultation with The next set of questions in Section 2 related to the feedback produced from wineries. A summated scale was used for these questions, based on the positive and negative feedback obtained from the winery. The positive and negative feedback responses were added together to produce a single scale item in the data analysis stage. Therefore, if a respondent answered “1” for negative winery feedback and “4” for positive winery feedback, the summate was “3” (i.e. -1+4=3). The scale items were derived from the Mohr & Nevin (1990) and Mohr et al., (1996) studies, as the feedback elements are a basis of collaborative communication.
The next few questions are regarding the feedback that the winery provides to the growers.
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Table 4.3: Questionnaire scale items regarding winery feedback
Please indicate by clicking the box that corresponds with your answer
How much negative feedback does this winery provide to you? How much positive feedback does this winery provide to you?
The next questions in Section 2 detailed the non-coercive communication attempts. Derived and adapted from Mohr & Nevin (1990) and Mohr et al., (1996) and scrutinised by wine industry experts, the scale items were as follows:
Table 4.4: Questionnaire scale items: non-coercive communication attempts
In their interaction with you, the winery often tries to influence YOUR attitudes and behaviours. Please estimate the frequency with which the winery‟s employees (e.g. winemakers, grower liaison staff, viticultural staff) use the following methods to influence YOU.
How frequently did the winery‟s employees make a recommendation that by following their suggestions, your business would be more profitable. How frequently did the winery‟s employees ask you to perform a certain operation, but didn‟t say what penalty may occur if you didn‟t do what they asked. How frequently did the winery‟s employees say you will be supplying grapes of a certain quality, but didn‟t give you specific information e.g. what crop level they would like, what spray regime they would like or other directions they would like you to take to grow those grapes.
The following division of Section 2 involved questions regarding trust. The scale items for trust were based on the Kumar et al., (1995) dimensions of trust and were compared and adapted using scale items from Walter et al., (2003), Bigne & Blesa (2003), Kingshott & Pecotich (2007), Kwon & Suh (2004), Morgan & Hunt (1994), and Petersen et al., (2005). The modified scale items were then scrutinised by wine industry experts to enhance the validity of the items. They are as follows:
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Table 4.5: Questionnaire scale items regarding trust
When things go bad, we believe that the winery will be ready and willing to offer us assistance and support. When making important decisions, the winery is concerned about our welfare.
When we share our problems with the winery we know that they will respond with understanding. We can count on the winery to consider how its decisions and actions will affect us.
When it comes to things that are important to us we can depend on the winery‟s support. Even when the winery gives us a rather unlikely explanation, we are confident that they are telling the truth.
The winery has often provided us information that has later proven to be incorrect. The winery keeps the promises that it makes to our business. Whenever the winery gives us advice on our business operations, we know that it is sharing its best advice. Our organisation can count on the winery to be sincere.
The next set of scale items were regarding satisfaction and were based on the scale items from Kwon & Suh (2004) but were adapted and compared to scale items from Walter et al., (2003) and Bigne & Blesa (2003), and scrutinised by wine industry experts. The scale items were as follows:
Table 4.6: Questionnaire scale items regarding satisfaction Please indicate how strongly you agree with the following statements:
We are very pleased with our working relationship with the winery. Generally we are very satisfied, with our overall relationship with the winery.
The relationship our business has with the winery has been an unhappy one. I am happy with the contract I have with the winery for my grapes.
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The final set of questions in Section 2 of the questionnaire contains scale items regarding power. The scale items were derived from Wilson & Vlosky (1998) and were adapted for the wine industry context. They were considered appropriate by wine industry experts. The scale items are as follows:
Table 4.7: Questionnaire scale items regarding power Please indicate how strongly you agree with the following statements:
We have to follow the winery‟s instructions or they will get their grapes from someone else. We are expected to follow the winery‟s instructions. We have influence over the winery‟s actions. The winery can, if it wanted to, severely penalise us if we are uncooperative. If we did not want to follow the winery‟s instructions or plans we could sell our grapes to another winery.
4.4 Data preparation and data analysis techniques The questionnaire data was compiled by the online survey web site company. The survey‟s data was downloaded as a Microsoft Office Excel file and uploaded into the statistical program SPSS (Statistical Package for Social Sciences). Prior to the Excel file upload into SPSS, each question in the survey was entered into SPSS, thereby allowing the uploaded Excel file data to correspond with the questions.
Upon completion of the upload of the Excel file into SPSS, the data was screened for validity. Analysis was performed using descriptive statistics, such as means and standard deviations, and graphically illustrated using box plots. Cases that contained incomplete responses, or responses that were outside ranges or had means or standard deviations that were not reasonable or believable, were deleted. The purpose of the screening was not only to remove missing answers or implausible responses but also to check the pattern of the missing data and why it was missing (Hair et al., 2006). A box plot analysis showed the missing data to be random and less than 5% of the data points (Hair et al., 2006).
A total of 444 returned responses were uploaded into SPSS and, following validity screening (incomplete, blatantly wrong, somewhat suspicious responses), 48 responses were deleted, leaving 396 valid responses. 78
4.4.1 Univariate Analysis Univariate analysis was used to determine the frequency, mean and modality of the descriptive variables in the data set. The descriptive variables were mainly contained in Sections 1 and 3 of the questionnaire and were based on questions regarding the demographics of the respondents‟ businesses and the details of the contracting arrangement between the respondent and the winery, such as contracting dollar amounts, price per tonne, length of contract, and volume of grapes supplied. The data was analysed via the univariate statistics to determine the demographics and contracting arrangements of the grape grower respondents with wineries. The univariate results are tabled in Chapters 5 and 6..
4.4.2 Multivariate Analysis Factors analysis, structural equation modelling and cluster analysis were the multivariate techniques used in the analysis of the research results.
Firstly, factor analysis was performed on the constructs used in the study (e.g. power, trust, satisfaction, collaborative communication dimension). Factor analysis is a data reduction technique that investigates the relationships between scaled metric variables and endeavours to understand the underlying factors (Malhotra et al., 2006; Hair et al., 2006). Each factor is then extracted and if a dimension extracts on one variable, then that variable is used as the sole variable in the analysis of that dimension. As such, the principle component analysis was used to reduce and eliminate variables that did not contribute to the factor, and confirmatory factor analysis (CFA) was used to validate the measurement model (Hair et al., 2006). CFA is performed during the structural equation modelling process via the statistical package SmartPLS to determine if the scale items correspond to the latent construct. Cronbach‟s alpha reliability coefficient was utilised to test the internal consistency of the model and composite reliability of the measurement (Werts et al., 1974). The coefficient describes how well a group of items focuses on a single construct with an index of 0.7 or higher considered preferable (Hair et al., 2006). However, it is argued that composite reliability index is more “... reliant in assessing convergent validity as it takes into account the relative weights of the indicators of the latent construct while Cronbach Alphas assume equal weight” (Gyau & Spiller, 2007, pg. 10). Convergent validity refers to whether the construct measures
79 what it is supposed to measure. This is performed by calculating the Average Variance Extracted (AVE) which assesses whether the construct variance can be explained by the indicators (Fornell & Larckner, 1981). The recommended smallest value is for each construct to be at least 0.5, which means that the indicator explains at least 50% of the variance (Bagozzi & Yi, 1988).
Structural Equation Modelling (SEM) is a statistical technique for testing and estimating causal relations using quantitative statistical data (Hair et al., 2006). The SEM process begins with the creation of a model based on the relevant academic theory and supporting research (Hair et al., 2006). In the case of this study, the relevant literature and the results of the exploratory research study provided the basis for the theoretical models which are exhibited in Chapter 3.
The technique used to test the model was Partial Least Squares (PLS) structural equation modelling. This technique, utilising SmartPLS software 2.01, allowed for the understanding of the relationship between the latent variables and was considered appropriate for the study due to the ability of PLS to handle structural equation modelling of small sample sizes; it uses less strict distributional assumptions than LISREL or AMOS would use (Chin, 1998; Joreskog & Wold, 1982; Ringle et al., 2005; Gyau & Spiller, 2007). Effectively it is a prediction-oriented, variance based approach to SEM (Liljander et al., 2009).
Confirmatory factor analysis (CFA) is also performed by SmartPLS while estimating the model, thereby allowing a set of quality statistics (such as Cronbach Alphas, mean and standard deviations) to be obtained. PLS is also a soft modelling form of structural equation modelling which “…iteratively estimates the parameters of latent variables” (Gyau & Spiller, 2007, pg. 9).
Under the soft modelling approach, there a two types of variables considered: the manifest and latent variables. Simply stated, the latent variables were the constructs identified in the literature, such as the collaborative communication elements (for example, formality, direct and indirect communication, etc.), trust, satisfaction; the manifest variables were the questionnaire items (scale items) used to test the latent variables. In the soft modelling approach, manifest variables that do not make a significant contribution to their respective latent variables; AVE, Cronbach Alpha, and
80 composite reliability were removed. The analysis is completed until all manifest variables are significant. A bootstrapping technique was then performed to gain a T- value for the paths between latent variables which allowed for significance testing of the paths. A bootstrapping re-sampling of 500 cases was used as per normal with this type of SEM (Gyau & Spiller, 2007).
The benefit of using PLS over other SEM techniques that use maximum likelihoods (such as LISREL or AMOS) is that PLS can estimate a model when as little as two manifest variables are used to measure the latent variable, in addition to the ability to estimate models with small samples sizes and models that do not have strict assumptions on residual distributions, such as this study (Dibben & Chin, 2005; Gyau & Spiller, 2007; Herath & Rao, 2009).
The testing of the SEM was performed by evaluating the inner and outer models. The outer model is evaluated by examining the individual item reliabilities‟ convergent validity. Factor loadings of at least 0.4 are considered significant and retained in the model (Hair et al., 2006; Gyau & Spiller, 2007). The internal consistency of the model was calculated by appraising the Cronbach Alphas and the composite reliability of the latent variables (Werts et al., 1974). A loading of greater than 0.7 from the Cronbach Alphas and 0.5 for the composite reliability is acceptable (Werts et al., 1974, Hair et al., 2006). The convergent validity of the latent variables is also measured by calculating the AVE, with a minimum of 0.5 recommended (Bagozzi & Yi, 1988).
The inner model is evaluated via the discriminant validity which details whether each latent variable is different from the other latent variables. To achieve this, a loading and cross loading matrix was obtained. The loadings were the Pearson correlation coefficients to their own latent variables. The loadings must be higher than the cross loadings (Gyau & Spiller, 2007). Another technique for measuring discriminate validity is by observing the square root of the AVE, which must be higher than the correlation between the latent variable and the other latent variables (Chin, 2001). Bagozzi (1984) suggests that the correlations between the different constructs in the model must be smaller than 0.8. Table 4.1 illustrates a summary of the statistical criteria for model estimation using PLS.
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Table 4.8: Statistical criteria for model estimation via PLS
Statistical Criterion Acceptable Fit Author
Convergent Validity 0.4 or greater Hair et al (2006)
Average Variance 0.5 or greater Bagozzi & Yi (1988) Extracted (AVE
Cronbach Alpha 0.5 or greater Cronbach, 1970; Gyau & Spiller, 2007
Composite Reliability 0.5 or greater Werts et al, 1974
Discriminant Validity* Less than 0.8 Bagozzi, 1994; Chin, 2001
*Correlation between the square root of AVE and correlation between constructs
4.5 Chapter summary This chapter outlined the design of the descriptive and causal research stage and the methodology employed. Due to the nature of grape growing in the Australian wine industry, a non-probability sampling technique was employed and quantitative data was collected from grape grower respondents via an online survey method, with assistance from regional grape grower associations and private companies that liaise with grape growers. The questionnaire instrument contained scale items derived from the marketing literature and these were modified for wine industry standards. Care was taken to pre-test the survey on grape growers to obtain external validity, and also to use wine industry experts to give opinions.
The chapter concluded with an outline of the statistical techniques used in the primary research study, including a detailed discussion on structural equation modelling.
As discussed above, this chapter illustrated the methodology utilised in the primary research study. The next chapter of the thesis, Chapter 5, discusses the results of the descriptive research study, which includes the descriptive statistics of the respondents‟ business operations and their trading relationships.
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Chapter 5: Descriptive statistics of respondents and trading relationships
5.1 Chapter outline Chapter 5 commences with a discussion of the results obtained from the descriptive stage of the study, i.e. the quantitative results from the questionnaire instrument. As detailed in the chapter title, the chapter will exhibit the descriptive statistics of the business relationship between the grape growers and the wineries, and descriptive, business related statistics of the grape growers.
The statistics that are presented in this chapter are gleaned from sections 1 and 3 of the questionnaire. As discussed in Chapter 4, section 1 of the questionnaire contained items regarding the business relationships growers had with the wineries and included questions relating to the number of years the grower was contracted to the winery, the tonnes of grapes supplied and the value and price per tonne of those grapes, the size of the winery and the type of ownership that the winery had, the region that the winery was in, and the number of other wineries to which the grower supplied. Section 3 of the questionnaire contained questions relating to the descriptive statistics of the grower respondents and contained questions regarding the size of their vineyards, the number of years the growers had been growing vines, the number of employees in the grape growing business and the region in which the grape growing business was located. The statistics from section 2 of the questionnaire relate to the estimation of the conceptual models and their various hypotheses and are discussed in Chapter 6.
The main purpose of this chapter is to benchmark the respondents‟ responses against other previous studies utilising the Australian wine industry and Australian wine industry statistics, to observe if the respondents are representative of the sample population. It was also of interest to examine if the grape grower respondents of this study are representative of grape growers in the Australian wine industry.
Firstly, the descriptive results of section 1 of the questionnaire are discussed.
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5.2 Section 1: Descriptive statistics of grower/winery relations.
5.2.1 Duration of relationship with winery As discussed in 5.1, section 1 of the questionnaire detailed the business relationships of the grower respondents. As discussed in Chapter 4, respondents had to focus on the business relationship that was most important to them. The mean number of years that growers had the relationship with the winery they were asked to focus on was 8.5 years and a standard deviation of 8.37 (n=396). The cumulative frequencies, shown in Table 5.1 below, illustrate that most of the relationships (approximately 42%) were less than or equal to five years. This length of relationship is supported by previous research on the Australian wine industry that suggest that typical grape supply contracts are between three and five years in length (Scales et al., (1995); Edmonds, (2000); Anderson, 2001; Hobley, 2007). It can be concluded that the respondents of this study are representative of the sample population in terms of the length of contract with wineries. However, this study observed the “best” winery relationship from the respondents‟ perspective. It would stand to reason that a “best” relationship would be ongoing and have a longer length, but the economic turmoil in the industry may be creating a situation where a “best” relationship is shorter rather than longer. However, the concept of “best” relationships being longer is speculation, and industry upheaval potentially may mean that any relationship is “best”. However, this is speculation.
Table 5.1: Years of contractual relationships between respondents and wineries
Years of Frequency % Cumulative % contract
5 167 42.2 42.2
6-10 105 26.5 68.7
11-15 71 17.9 86.6
16+ 53 13.4 100
5.2.2 Volume of grapes supplied to winery A question was posed to respondents to determine the amount (tonnes) of grapes supplied to the winery. The mean result was 214.4 tonnes with a standard deviation of 84
493.0 (n= 396) which illustrates that the statistics were highly distributed and the high score for the mean result is manifest in the large number of respondents who supplied more than 700 tonnes, as opposed to other volume categories such the 300 to 700 tonne categories. Table 5.2 exhibits these results further and illustrates that the majority of the respondents supplied less than, or equal to, 100 tonnes of grapes (67.7% of respondents). This result is in line with that of Hobley (2007) who found that the majority of grape growers supply less than 100 tonnes of grapes to a winery. Therefore, it can be stated that the respondents of this study are representative of the sample population in terms of the volume of grapes supplied to wineries.
Furthermore, it appears that the “best” relationship a respondent has with a winery involves a smaller rather than larger volume of grapes and perhaps, though this is speculation, smaller volumes may mean that “best” relationships with wineries are a result of the production of quality, which results in smaller yields, as opposed to quantity of grapes. On the other hand, as shown in Table 5.11, 53.3% of respondents‟ vineyard size were less than or equal to 25 acres, which would result in smaller volumes of grapes being supplied.
Table: 5.2: Volume of grapes supplied to winery by grape grower respondents
Volume of Frequency % Cumulative % grapes (tonnes)
100 268 67.7 67.7
101-300 57 11.9 79.6
301-500 24 4.3 83.9
501-700 15 6.3 90.2
701+ 32 9.8 100
5.2.3 Value of grapes supplied to winery by respondents Section 1 of the questionnaire contained a question asking the respondents to detail the value of the grapes they supplied to the winery. The statistics showed a mean score of $138,916 with a standard deviation of $276,133 (n=396). The standard deviation score
85 illustrates a wide distribution of responses. Table 5.3 illustrates the results further and shows that approximately 43% of all respondents‟ grapes were supplied at a value of less than or equal to $50,000, and that approximately 75% of all respondents supplied grapes less than or equal in value to $100,000. The large number of responses in the $500,000 plus category appears to be elevating the mean. These results cannot be benchmarked against other similar studies as the value of the produce from a “best” relationship had not been examined in previous studies. Overall it can be observed that the “best” relationship a respondent had with a winery involved receiving a relatively small amount of money (i.e., less than or equal to $50,000).
Table 5.3: Value of grapes supplied to winery by respondents
Value of grapes Frequency % Cumulative % ($)
50,000 170 42.9 42.9
50,001- 100,000 123 31.6 74.5
100,001- 500,000 85 21 95.5
500,001 + 18 4.5 100
5.2.4 Average price per tonne of grape supplied to winery Descriptive statistics of the trading relations between the grape grower respondents and the wineries included data for the average price per tonne of the grapes supplied to the winery. The descriptive statistics showed a mean score of $1409.4 and a standard deviation of $916.25 (n= 396). Further analysis of the data, shown in Table 5.4, illustrates that 32% of all respondents received less than or equal to $1000 per tonne for their grapes, while 68% of respondents received $1001 and above for their grapes. The average price per tonne is above the cost of production for grapes, which is between $250 and $400 per tonne (Davidson, 2010); however, no other studies have observed the average price per tonne supplied to wineries and thus, benchmarking this statistic is not possible.
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Table 5.4: Price per tonne of grapes supplied to the winery by respondents
Price per tonne Frequency % Cumulative % ($)
500 75 18.9 18.9
501- 1000 52 13.1 32.0
1001- 1500 136 34.3 66.3
1501+ 133 33.7 100
5.2.5 Other wineries supplied and the amount of grapes supplied to those wineries. Section 1 of the instrument posed questions mostly involving the business relationship that was most important to the grape grower‟s business. Therefore, the questions were specifically asked with respect to that relationship (for example, price per tonne, value of grapes, and volume of grapes). However, section 1 also posed two questions relating to the relationships that growers had with other wineries, specifically how many other business relationships the growers had and the amount of grapes that they supplied to those other wineries. Respondents‟ results showed that they supplied an average (mean) of 1.92 other wineries and approximately 22% of their total grape production went to those other wineries (n=396). Further analysis of the data, illustrated in Tables 5.5 and 5.6, shows that approximately 56% of all the respondents supplied fewer than two other wineries and approximately 63% of the respondents supplied less than or equal to 25% of their production to the other wineries. These results are consistent with those of Hobley (2007), who found that the majority of grape growers have fewer than two contracts. However, Hobley (2007) only observed relationships as contracts, as opposed to other types of relationships such as casual relationships not based on contracts or spot market transactions. Overall, it can be surmised that the respondents were representative of the sample frame in terms of the number of relationships they had with wineries.
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Table 5.5: Number of other wineries to which respondents supplied grapes
Number of other Frequency % Cumulative % wineries
Less than 2 219 55.5 55.5
2-4 159 40.2 95.7
More than 4 18 4.3 100
Table 5.6: Percentage of grape production supplied to the other wineries
Percentage of Frequency % Cumulative % grape production (%)
25 248 62.6 62.6
26- 50 122 30.8 93.4
50+ 26 6.6 100
5.2.6 Business details of the winery that was supplied grapes Much of the discussion of this chapter has been based on the details of trading relations between the respondent and wineries supplied with grapes, including the price and dollar amounts that the respondent received and the volumes of grapes supplied. In section 1 of the questionnaire, the respondents were asked the business details of the winery to which they were supplying grapes. Specifically, they were asked questions regarding the size of the winery, the ownership of the winery and the wine region in which the winery was located.
Respondents indicated that the majority of the wineries that they focused on in the questionnaire were privately owned, small to medium sized enterprises (illustrated in Tables 5.7 and 5.8). The wineries were located in all states in Australia, with the Barossa Valley being the region in which the wineries were mostly located (illustrated in Table 5.9). While no benchmarking figures are available for the size parameters of 88 wineries, there are 2420 wineries in Australia (Winetitles, 2010) and less than 10% are publicly owned. However, the largest grape purchasers are the large, privately owned companies. Seven the top 20 wine companies are privately owned and process 77% of the grapes in Australia. Furthermore, Constellation Wines Australia and Fosters Wine Group processed approximately 30% of the grapes from the 2009 vintage (Winetitles, 2010). However, the respondents focused on the “best” relationship and the data in Table 5.7 shows that the winery was privately owned. Due to the fact that approximately 10% of wineries in Australia are publicly owned, it can be surmised that the respondents are representative of the sample frame in terms of the ownership of the winery that constitutes their best relationship. Most privately owned wineries are small to medium sized, and therefore the data in Table 5.8 reinforces the notion that the winery relationships are representative of the sample frame.
Table 5.9 illustrates that the wine region in which the wineries were located was mainly in the Barossa Valley, Riverland and Riverina (40% of responses). Furthermore, Table 5.11 shows the locations of the wineries by state and the table illustrates that approximately 80% of all wineries were located in South Australia , NSW and Victoria. Winetitles (2010) states that 77% of all wineries are located in those three states, therefore, it can be surmised that the respondents were dealing with wineries that were representative of wine production in Australia and are indicative of the target sample population. Interestingly, 7.1% of respondents stated that they did not know in which region the winery they supplied was located.
Table 5.7: Ownership of the winery to which respondents supplied grapes
Ownership of Frequency % Cumulative % the winery
Privately owned 239 60.4 60.4
Publicly owned 126 31.8 92.2
Don‟t know 31 7.8 100
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Table 5.8: Size of the winery to which respondents supplied grapes
Size of the Frequency % Cumulative % winery
Small to medium 243 61.4 61.4
Large 127 32.1 93.5
Don‟t know 26 6.5 100
Table 5.9 Wine region winery was located in
Wine region Frequency % Cumulative %
Barossa Valley 64 16.2 16.2
Riverland 49 12.4 28.5
Riverina 45 11.4 39.9
McLaren Vale 33 8.3 48.2
Don‟t Know 28 7.1 55.3
Hunter Valley 24 6.1 61.4
Yarra Valley 21 5.3 66.7
Mornington 11 2.8 69.4 Peninsula
Clare Valley 11 2.8 72.2
Adelaide Hills 11 2.8 75.0
Margaret River 10 2.5 77.5
Coonawarra 9 2.3 79.8
Goulburn Valley 9 2.3 82.1
Swan District 7 1.8 83.8
Granite Belt 7 1.8 85.6
Eden Valley 7 1.8 87.4
Rutherglen 7 1.8 89.1
Great Southern 5 1.3 90.4
Tasmania 5 1.3 91.7
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Orange 4 1.0 92.7
Mudgee 4 1.0 93.7
Bendigo 3 .8 94.4
Limestone Coast 3 .8 95.2
Heathcote 3 .8 96.0
Geelong 2 .5 96.5
Pyrenees 2 .5 97.0
Pemberton 2 .5 97.5
Langhorne Creek 2 .5 98.0
King Valley 2 .5 98.5
Blackwood 1 .3 98.7
Tumbarumba 1 .3 99.0
Padthaway 1 .3 99.2
Gippsland 1 .3 99.5
Manjimup 1 .3 99.7
Canberra 1 .3 100.0
Table 5.10: State wineries were located in
State Frequency % Cumulative %
South Australia 192 48 48
NSW 87 22 70
Victoria 50 13 83
Western Australia 26 6.7 89.7
Queensland 7 1.9 91.6
Tasmania 5 1.4 93
Don‟t Know 28 7 100
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5.2.7 Summary of trading relations of grape grower respondents The respondents in the questionnaire detailed their trading relationships with the winery they were asked to focus on and the other wineries that they traded with. This section of the questionnaire (section 1) has highlighted numerous results of interest. A summary of the results is shown in Table 5.11.
Table 5.11: Summary of the trading relationship of respondents and wineries Duration of relationship Less than or equal to 5 years
Volume of grapes supplied Less than or equal to 100 tonnes
Value of grapes supplied Less than or equal to $50,000
Price per tonne of grapes supplied $1000-1500
Ownership of winery Privately owned
Size of winery Small to medium
Wine region of winery Barossa Valley
Other wineries supplied Less than 2
Percentage of grapes supplied to other Less than or equal to 25% wineries
5.3 Section 3: Descriptive statistics of respondents The previous section of this chapter, 5.2, discussed the trading relationship details between the respondents and the winery. The statistics from this section (5.2) were derived from section 1 of the questionnaire and contained information relating to price per tonne, volume of grapes etcetera. Section 3 of the questionnaire posed questions to the respondents regarding the size and nature of their businesses. This part of the chapter will exhibit the details of the respondents‟ (grape growers) business, commencing with a discussion of the size of their vineyards. As previously mentioned, section 2 of the questionnaire will be discussed in Chapter 6.
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5.3.1 Size of the respondents‟ vineyards Respondents were asked to complete a questionnaire item on the size of their vineyards. The results showed a mean vineyard size of 58.1 acres with a standard deviation of 111.6 (n=396). Analysis of the results, exhibited in Table 5.11, shows that 53.3% of respondents have vineyards less than or equal to 25 acres. Furthermore, Table 5.11 shows that over 75% of respondents have vineyards less than or equal to 50 acres. This is similar to the evidence supplied by Hobley (2007) and Phylloxera Board SA (2010) who commented that the majority of grape growers in Australia, and specifically in South Australia, had vineyards of less than 50 acres. It can be surmised that the respondents are representative of the sample frame in terms of the size of their vineyards.
Table 5.12: Size of respondents vineyards in acres
Size (acres) Frequency % Cumulative %
25 211 53.3 53.3
26-50 87 22 75.3
51- 100 43 10.9 86.2
100+ 55 13.8 100
5.3.2 Number of years respondents operating their viticultural business Section 3 of the questionnaire posed an item to respondents asking them to detail the number of years they had been operating their viticultural business. Results showed that respondents had been running their viticultural business for an average of 19.5 years with a standard deviation of 13.9 years (n=396). Further analysis of the data, exhibited in Table 5.12, illustrates that 47.5% of respondents had been operating their business for less than or equal to 15 years. Table 5.12 also shows that a large number of respondents had been operating their business for 26 or more years, which accounts for a higher mean score. The data in Table 5.12 illustrates that 71% of respondents had operated their businesses for less than 20 years. While no industry data was available to benchmark this result, a similar study (Hobley, 2007) found that 78% of grape grower respondents had operated their businesses for less than 20 years. Therefore, it can be concluded that the respondents are representative of sample population in terms of the length of business operation. A potential reason for the majority of respondents running 93 their business for less than 15 years may be that a boom in managed investment schemes in grape production in the late 1990s led to accelerated grape plantings and, therefore, the establishment of many grape growing businesses (Speedy, 2006).
Table 5.13: Number of years respondents operation of business
Years Frequency % Cumulative %
10 34 8.6 8.6
11-15 154 38.9 47.5
16-20 94 23.7 71.2
21-25 40 10.1 81.3
26+ 74 18.7 100
5.3.3 Number of people employed by respondents‟ businesses Respondents were asked to detail the number of employees that worked for their business. Respondents were asked to include all people who were actively working for the business, including the owner. A mean score of 2.7 people with a standard deviation of 3.0 (n= 396) was shown in the statistics. Further analysis, exhibited in Table 5.13, shows that 85.4% of respondents‟ businesses had less than or equal to 3 employees. While no industry statistics were available to benchmark this result, Hobley (2007), in a study utilising a similar sample frame, found that 80% of grape growers had fewer than five employees. With this in mind, it is reasonable to assume that the respondents are representative of the sample population in terms of the number of employees.
Table 5.14: Number of people employed by respondents‟ businesses
Number of Frequency % Cumulative % people
3 338 85.4 85.4
4-6 45 11.4 96.8
7+ 13 3.2 100
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5.3.4 Wine region location of respondents‟ businesses Respondents were asked in section 3 of the questionnaire to list in which wine region their businesses were located. The responses, exhibited in Table 5.14, show that 13.5% of respondents had their businesses located in the Riverland and that respondents‟ businesses were located in all states of Australia. Furthermore, approximately 25% of respondents were located in the Murray Valley Irrigation zone which encompasses the Riverland and Riverina grape growing regions. While no industry data was available on the number of grape growers in individual regions, investigations found that approximately 20-30% of all grape growers in Australia are located in the Murray Valley Irrigation zone (Davidson, 2010). Furthermore, 30% of all grapes harvested in the 2009 vintage came from these two regions (ABARE, 2010) and 45% of all respondents resided in South Australia. In addition to this, approximately 50% of all grape production in the 2009 vintage came from South Australia, which is reflected in the results, particularly Table 5.16, which shows that 50% of all respondents came from South Australia (Winetitles, 2010). With these figures in mind, it is reasonable to assume that the respondents are representative of the sample frame in terms of the location of their grape growing businesses.
Table 5.15: Wine region location of respondents viticultural businesses
Wine Region Frequency % Cumulative %
Riverland 50 13.5 13.5
Barossa Valley 48 12.9 26.4
Riverina 44 11.9 38.3
McLaren Vale 34 9.2 47.4
Yarra Valley 19 5.1 52.6
Adelaide Hills 17 4.6 57.1
Hunter Valley 16 4.3 61.5
Clare Valley 13 3.5 65.0
Mornington 12 3.2 68.2 Peninsula
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Margaret River 9 2.4 70.6
Swan District 8 2.2 72.8
Coonawarra 8 2.2 74.9
Rutherglen 8 2.2 77.1
Mudgee 7 1.9 79.0
Tasmania 6 1.6 80.6
Goulburn Valley 6 1.6 82.2
Great Southern 6 1.6 83.8
Orange 6 1.6 85.4
Granite Belt 6 1.6 87.1
Heathcote 5 1.3 88.4
Eden Valley 5 1.3 89.8
Langhorne Creek 4 1.1 90.8
Tumbarumba 4 1.1 91.9
King Valley 4 1.1 93.0
Limestone Coast 4 1.1 94.1
Geelong 3 .8 94.9
Wrattonbully 3 .8 95.7
Cowra 3 .8 96.5
Canberra 2 .5 97.0
Pyrenees 2 .5 97.6
Pemberton 2 .5 98.1
Bendigo 2 .5 98.7
Manjimup 2 .5 99.2
Blackwood 1 .3 99.5
Padthaway 1 .3 99.7
Gippsland 1 .3 100.0
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Table 5.16: State respondents were located in
State Frequency % Cumulative %
South Australia 186 50 50
NSW 89 24 74
Victoria 56 15 89
Western Australia 28 7.6 96.6
Queensland 6 1.7 98.3
Tasmania 6 1.7 100
5.3.5 Technical viticultural qualifications of respondents Section 3 of the questionnaire asked respondents to list the viticultural qualifications that they had obtained. Table 5.15 exhibits the qualifications of respondents and shows that 67.4% of respondents had no formal qualifications (n=396). While no industry statistics were available regarding the viticultural qualifications of grape growers in Australia, a similar study found that 65% of grape growers had a technical, bachelor or postgraduate qualification (Hobley, 2007). However, Hobley (2007) observed whether growers had these qualifications and not whether these qualifications were viticulturally based.
Table 5.17: Viticultural qualification of respondents
Qualification Frequency % Cumulative %
None 267 67.4 67.4
TAFE (technical 66 16.7 84.1 qualification)
Bachelor degree 29 7.3 91.4
Postgraduate degree 11 2.8 94.2
Other 23 5.8 100
(training seminars, short courses)
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5.3.6 Summary of descriptive statistics of respondents Section 3 of the questionnaire was designed to highlight the description of the grape grower respondents. Table 5.16 provides a summary of the descriptive statistics of these respondents. What can be observed is that, in relation to grape trading terms, the “best” relationship is a small length contract, for a small volume of grapes that has a relatively small value but the price per tonne is relatively high. Therefore, it can be surmised that the “best” relationship is one that provides the highest price per tonne of the grapes.
Table 5.18: Summary of descriptive statistics of respondents Size of Vineyards Less than or equal to 25 acres
Years of business operation 11-15
Number of people employed by business Less than or equal to 3
Wine region location of business Riverland
Viticultural qualifications of respondent None
5.4 Chapter Summary Chapter 5 detailed the univariate statistics of the questionnaire. Therefore, the chapter dealt with sections 1 and 3 of the questionnaire and provided statistics of the description of the trading relationships between the respondent and the winery and the descriptive statistics of the respondents and their businesses. Sections 1 and 3 of the questionnaire have now been discussed. Section 2 of the questionnaire, which relates to the conceptual models and the examination of hypotheses, is the topic of discussion of the next chapter, which is Chapter 6.
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Chapter 6: An integrated model of buyer-seller relationships in the Australia wine industry
6.1 Chapter outline This chapter presents the main research data collection including the testing of the hypotheses and conceptual models, as outlined in Chapter 3, providing an integrated model of buyer-seller relationships in the Australian wine industry.
The previous chapters of this thesis have followed a logical progression to the estimation of two structural equation models (SEM), which are the integrated model discussed above, and an alternative model. Previous chapters presented and discussed literature. Exploratory qualitative research was performed and analysed which allowed for the creation of the conceptual models with various paths between variables and hypotheses formulated. Questionnaire scale items to test the conceptual models were then selected from the literature and modified to be relevant to the context of the research. This chapter involves statistically estimating the conceptual models, thereby presenting an integrated model and an alternative model.
This chapter takes a two-step process to the SEM process. In the first step, a measurement model process is presented whereby the questionnaire variables are examined via exploratory factor analysis to see if they represent the constructs. The second step of the process involves examining how each of the constructs are associated to each other, thereby presenting an integrated model and an alternative model which were tested using Partial Least Square Regression. Further analysis in the form of cluster analysis is presented at the end of the chapter.
6.2 Measurement model of constructs In Chapter 3, conceptual models of communication elements between grape growers and winemakers, their effect on trust and satisfaction (relationship quality), and the influence of power asymmetry, was formulated. The first step to test the models was to take the dimensions of communication, trust, satisfaction and power, and subject them to Exploratory Factor Analysis utilising Principle Component Analysis (PCA). This 99 process was performed to identify the formation of the constructs and to discard items which did not contribute to the factor (Anderson & Gerbing, 1988; Hobley, 2007). All variables with factor loadings above 0.5 were retained. This process revealed that all the dimensions of communication, trust, satisfaction and power were extracting on one component except the dimension of communication modality. Modality of communication was hypothesised in Chapter 3 as being either face-to-face or non-face- to-face communication. Therefore, the hypothesis was dealing with the notion that face- to-face communication was purely “real time” face-to-face communication between two actors and seminar communications, and non-face-to-face communication was concerned with modes that were not face-to-face, as for example email, newsletters and telephone communications. The PCA results revealed that the construct communication modality was extracting on more than one component, and that it was extracting not on the “face-to-face versus non-face-to-face” dimensionality, but on a “direct” or “indirect” dimensionality. The PCA showed that modalities such as personal direct email, telephone and face-to-face dimensions were extracting together and as they involved direct communication from one person to another, as opposed to communication that is directed to a group of individuals. It is warranted to discuss those modalities as direct communication. The other modes, such as newsletters, group written letters, seminars and other modes of communication, could be discussed as indirect modes as they are not from one actor to one actor, but from one actor to groups of actors.
The next stage of the analysis involved the use of the Partial Least Squares (PLS) approach to Structural Equation Modeling (SEM) to test the hypotheses. In the PLS approach to SEM, the fit of the model is estimated via the inner and outer models.
6.2.1 Evaluation of the outer model The outer model is evaluated by examining the individual item reliabilities and convergent validity of the model. The individual item reliabilities were examined through the factor loadings of the items on their respective constructs. Only items with factor loadings of at least 0.4 were considered significant and retained in the model (Hair et al. 2006). Thus, many of the items were not considered significant and were excluded from the analysis, particularly related to the communication dimension. The results of the outer model evaluation are exhibited in Table 6.1. As outlined in Chapter 4, the internal consistency of the model was assessed via the Cronbach Alpha 100
(Cronbach, 1970) and the composite reliability of the measurements (Werts et al., 1974). These indicators rank from 0 (absence of homogeneity) to 1 (maximum homogeneity), with a usual criteria of both indexes to be greater than 0.7. Table 6.1 illustrates that all composite reliability indices range from 0.784 to 0.944 and the Cronbach Alphas range from 0.702 to 0.932, thereby satisfying the recommended thresholds.
Table 6.1: Outer model evaluation of collaborative communication dimensions, trust, satisfaction and power.
A B C D E F
Variables and indicators Factor Comp Cronbach AVE loading reliability
Feedback 1.000 1.000 1.000
Commfeed1 How much feedback do you 1.000 provide to this winery? (summate of neg and positive feedback
Formality 0.863 0.784 0.551
Commform1 When working with winery, 0.567 formal comm vs casual word or mouth comm
Commform3 The winery‟s expectations of 0.693 us are communicated in detail.
Commform4 The terms of our business 0.781 relationship with the winery have been explicitly put into words and discussed.
Commform5 Information sharing on 0.889 important issues has become crucial to maintaining this
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A B C D E F
Variables and indicators Factor Comp Cronbach AVE loading reliability
partnership.
Indirect communication 0.789 0.712 0.667
Commnews Newsletter communication 0.735
Commsemin Seminars communication 0.891
Direct communication 0.853 0.749 0.748
Comcomp Computer: email 0.759 communication
Commface Face-to-face communication 0.960
Non coercive 0.821 0.702 0.699 communication attempts
Commiflu2 How frequently did the 0.881 winery‟s employees ask you to perform a certain operation, but didn‟t say what penalty may occur if you didn‟t do what they asked.
Comminflu3 How frequently did the 0.786 winery‟s employees say you will be supplying grapes of a certain quality, but didn‟t give you specific information e.g. what crop level they would like, what spray regime they would like or other directions they would like you to take to grow those
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A B C D E F
Variables and indicators Factor Comp Cronbach AVE loading reliability
grapes.
Satisfaction 0.900 0.851 0.696
Satisf1 We are very pleased with our 0.904 working relationship with the winery.
Satisf2 Generally we are very 0.920 satisfied, with our overall relationship with the winery.
Satisf3 The relationship our business 0.753 has with the winery has been an unhappy one. (RS)
Satisf 5 I am happy with the contract I 0.740 have with the winery for my grapes.
Trust 0.944 0.932 0.655
Trust 1 When things go bad, we 0.833 believe that the winery will be ready and willing to offer us assistance and support.
Trust 2 When making important 0.868 decisions, the winery is concerned about our welfare.
Trust 3 When we share our problems 0.865 with the winery we know that they will respond with understanding.
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A B C D E F
Variables and indicators Factor Comp Cronbach AVE loading reliability
Trust 4 We can count on the winery 0.816 to consider how its decisions and actions will affect us.
Trust 5 When it comes to things that 0.825 are important to us we can depend on the winery‟s support.
Trust 6 Even when the winery gives 0.802 us a rather unlikely explanation, we are confident that they are telling the truth.
Trust 8 The winery keeps the 0.622 promises that it makes to our business.
Trust 9 Whenever the winery gives 0.776 us advice on our business operations, we know that it is sharing its best advice.
Trust 10 The winery offers me a fair 0.799 and reasonable price for my grapes.
Power 0.784 0.711 0.611
Power 1 We have to follow the 0.798 winery‟s instructions or they will get their grapes from someone else.
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A B C D E F
Variables and indicators Factor Comp Cronbach AVE loading reliability
Power 2 We are expected to follow the 0.690 winery‟s instructions.
Power 3 We have influence over the 0.880 winery‟s actions.
6.2.2 Evaluation of the inner model The first criterion used to measure the inner model was the discriminant validity. As discussed in Chapter 4, the discriminant validity measures whether every construct is significantly different from the other measures. To analyse this, loadings and cross loadings matrices were obtained, whereby the loadings are the Pearson correlation coefficients to their own constructs (Chin, 2001; Gyau & Spiller, 2007) . All loadings should be higher than the cross loadings which was the case in this study and is shown in Table 6.2.
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Table 6.2: Loadings and cross loadings of indicators and constructs
Direct com Formality Indirect com Noncoercv Power Satisfaction Trust Wineryfeed
Commcomp 0.7256 0.1788 0.1184 0.0026 -0.0641 0.0437 0.0561 -0.0320
Commface 0.9850 0.1006 -0.0246 -0.0616 -0.1148 0.1594 0.2342 0.1228
Commfeed1 0.0984 0.3327 -0.0251 -0.0990 -0.3284 0.5431 0.5603 1.0000
Commform1 -0.0831 0.5673 0.2078 0.0777 0.1973 0.1161 0.0564 0.1522
Commform3 0.1175 0.6934 0.3508 -0.0145 0.2638 0.1552 0.0185 0.1312
Commform4 0.1111 0.7808 0.3144 -0.0146 0.1244 0.2110 0.1310 0.2350
Commform5 0.1325 0.8887 0.2366 -0.1757 -0.0877 0.4489 0.3149 0.3410
Comminflue2 -0.0619 -0.1013 -0.0915 0.8810 0.1674 -0.2662 -0.1024 -0.0791
Comminflue3 -0.0202 -0.0769 0.0088 0.7858 0.1037 -0.1819 -0.1231 -0.0884
Commnews -0.0211 0.2168 0.7350 0.0078 0.1773 0.0172 -0.1019 0.0058
Commsemin 0.0201 0.3158 0.8907 -0.0844 0.1471 0.1062 -0.0933 -0.0387
Power1 -0.1160 -0.0075 0.0209 0.2395 0.7680 -0.3747 -0.3366 -0.2265
Power2 -0.0059 0.1602 0.1721 0.0255 0.6703 -0.1981 -0.2545 -0.1503
Power3 -0.0989 0.0171 0.2248 0.0874 0.7795 -0.3832 -0.5363 -0.3098
Satisf5 0.0701 0.3689 0.1527 -0.1838 -0.2562 0.7399 0.5227 0.3751
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Direct com Formality Indirect com Noncoercv Power Satisfaction Trust Wineryfeed
Satisf1 0.1659 0.3677 0.0698 -0.2603 -0.4392 0.9074 0.7612 0.5295
Satisf2 0.1438 0.3390 0.0463 -0.2173 -0.4341 0.9201 0.7335 0.5366
Satisf3 0.0895 0.2330 0.0249 -0.2547 -0.3567 0.7529 0.5142 0.3356
Trust1 0.1726 0.1779 -0.0795 -0.0560 -0.4272 0.5862 0.8331 0.4372
Trust10 0.1643 0.2478 -0.0608 -0.1388 -0.4271 0.6645 0.7992 0.4393
Trust2 0.1752 0.1341 -0.1762 -0.0717 -0.5033 0.6197 0.8680 0.4797
Trust3 0.1669 0.2217 -0.1062 -0.1424 -0.4650 0.6394 0.8652 0.5303
Trust4 0.1879 0.1702 -0.0729 -0.0764 -0.4557 0.5623 0.8252 0.4417
Trust5 0.2200 0.2191 -0.1389 -0.0698 -0.4458 0.6353 0.8645 0.4919
Trust6 0.1449 0.1345 -0.2338 -0.0358 -0.4758 0.5882 0.8023 0.4555
Trust8 0.1453 0.2361 0.0314 -0.2408 -0.3169 0.6665 0.6225 0.3353
Trust9 0.1705 0.3194 0.0316 -0.1740 -0.4076 0.6921 0.7756 0.4450
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Another criterion for measuring the discriminant validity is that the square root of the AVE which must be greater than the correlation between the construct and the other constructs in the study (Chin, 2001). This is shown in Table 6.2. The diagonal in the table displays the AVE square roots instead of the usual values of “1”. This is known as the Fornel Larcker Test (Fornel & Larcker, 1981; Gyau & Spiller, 2007). Bagozzi (1994) suggests that the correlations between the coefficients in the model must be smaller than 0.8. This is the case in Table 6.3.
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Table 6.3: Correlations of the latent variables and the AVE square roots
Direct Formality Indirectcom Noncoercv Power Satisfaction Trust Wineryfeed comm
Direct 1.0000 comm
Formality 0.1246 1.0000
Indirectcom 0.0043 0.3333 1.0000
Noncoercv -0.0522 -0.1080 -0.0572 1.0000
Power -0.1122 0.0532 0.1923 0.1665 1.0000
Satisfaction 0.1460 0.3937 0.0851 -0.2735 -0.4522 1.0000
Trust 0.2127 0.2525 -0.1168 -0.1326 -0.5420 0.7717 1.0000
Wineryfeed 0.0984 0.3327 -0.0251 -0.0990 -0.3284 0.5431 0.5603 1.0000
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6.2.3 Results of the structural model To evaluate the hypotheses that were formulated from the literature and exploratory research study (and highlighted in Chapter 3) and formed part of the conceptual model, the R2 and the significance of the paths were used. A graphical representation of the model is presented below in Figure 6.1.
Figure 6.1 Conceptual model of grape grower perceptions of relationship quality in the Australian wine industry
The significance of the path‟s coefficients was determined using a bootstrapping method with 1000 samples. The significance was then determined by using a one tail Student‟s T distribution test, at a 0.5 significance level. The R2 measured the construct variance explained by the model. Good fit exists when there is high R2. The R2 for the two dependent variables in the model was 0.597 for trust and 0.587 for satisfaction which indicated that the model provided a good fit for the latent constructs for use in Partial Least Square Regression in this type of study (i.e. non time series study) (Chin, 2001; Gyau & Spiller, 2007). Table 6.4 illustrates the results of the structural model 110 which includes the data for the confirmation (or otherwise) of the hypotheses. Table 6.4 lists the T-Statistics and therefore shows whether the hypotheses were significant or otherwise.
Table 6.4: Results of the structural model
Hypotheses Constructs Expected Sign Beta T-Statistic coefficients H1 Direct Com→Trust + 0.111** 3.033
H2 Direct Com→Sat + 0.035 0.908
H3 Indirect - -0.101** 1.716 Com→Trust
H4 Indirect Com→Sat - 0.063 1.193
H5 Feedback→Trust + 0.358** 7.520
H6 Feedback→Sat + 0.327** 6.085
H7 Noncoerc→Trust - -0.151** 3.551
H8 Noncoerc→Sat - -0.011 0.268
H9 Formality→Trust - 0.169** 3.820
H10 Formality→Sat - 0.261** 5.144
H11 Power→Trust - -0.402** 9.303
H12 Power→Sat - -0.342** 7.403
** Significant at p<0.05,
The results in Table 6.3 show the confirmation of H1, H3, H5, H6, H7, H11 and H12 and the rejection of H2, H4, H8, H9, 10. A graphical representation of the results is presented in Figure 6.2 below.
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Figure 6.2 A graphical representation of the of main structural equation model results
** Significant at p<0.05, Solid lines represent affirmed hypotheses, dashed lines represent rejected hypotheses.
6.3 Consideration of structural model results The structural model has illuminated numerous results. Of the 12 hypotheses, seven hypotheses were confirmed and accepted while five were rejected. Of interest were the five rejected hypotheses and the reasons for their rejection. This was done because the link between the two constructs was statistically insignificant (i.e. p> 0.05) and the path was testing the influence that elements of communication, in this case indirect and direct communication and non-coercive communication attempts, have on satisfaction. Therefore, it appears that the construct of satisfaction is a central theme to the rejected hypotheses.
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The central theme of satisfaction can be put into a wine industry context. As discussed in Chapter 1 and 2, the Australian wine industry is suffering economic hardship characterised by (apart from other reasons) an oversupply of grapes. This oversupply is leading to hardship being felt by growers due to reduced prices per tonne for their grape products. In many cases, growers were receiving below or close to below cost prices (Davidson, 2010). This has led to the industry proposing that 20,000 hectares, (approximately 20%) of grape vines, be removed due to the unsustainably high levels of grape production (Henry, 2009). It stands to reason that, regardless of the elements of communication between the two actors, the price that growers receive for their grapes is so low that they cannot be satisfied in any way by the relationship. This argument is further validated by the fact that the power asymmetry was having a very strong negative influence on trust and satisfaction (H11 and H12), evident in high beta coefficients and T-statistics shown in Table 6.3. As postulated in Chapter 1 and discussed in Chapter 2, satisfaction was an element of the relationship that was of interest to observe, particularly in view of the low grape prices received in the industry, and other industry related issues.
In this study, relationship quality was measured as a multi-dimensional higher order construct consisting of trust and satisfaction. Authors such as Crosby et al. (1990), Dorch et al. (1997), Kim & Cha (2002) and Kim et al. (2006)] empirically tested relationship quality, mostly via SEM and other multi-variate regression techniques, using trust and satisfaction a separate constructs, and they concluded that higher levels of trust and satisfaction in the model corresponded with higher levels of relationship quality. However, Scheer & Stern (1992) and Leuthesser (1997) empirically tested relationship quality as a uni-dimensional construct whereby the construct of relationship quality consisted of latent variables of trust and satisfaction. SEM literature considered whether alternative estimation (also known as two step model estimation) could be performed in order to observe which model best fits the data concerned (Joreskog & World, 1982; Anderson, & Gerbing, 1988; McDonald & Ho, 2002). In this instance, it would be of interest to observe a model which estimated relationship quality as a uni-dimensional construct as opposed to a multi-dimensional one, thereby satisfying a theoretical and methodological concern.
As such, the constructs exhibited in Table 3.1 would directly affect relationship quality in the alternative model as opposed the multi-dimensional affect shown in Table 3.1. Theoretically, the hypotheses would remain the same, although each independent
113 variable in the model (i.e. power, collaborative communication elements) would affect the singular dependent variable (i.e. relationship quality). Therefore, the alternative model hypotheses would be:
H1a. Face-to-face (direct) modes of communication positively influence relationship quality.
H2a. Non-face-to-face (non direct) modes of communication negatively influence relationship quality.
H3a. Uni-directional communication (feedback) from the winery positively influences relationship quality.
H4a. Non-coercive communication attempts from the winery negatively influence relationship quality.
H5a. Formality of communication from wineries negatively influences relationship quality.
H6a. A power asymmetry favouring the winery is decreasing grape growers‟ perception of relationship quality.
A graphical representation of the alternative model is presented in Figure 6.3
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Figure 6.3 Alternative model based on uni-dimensional estimation of relationship quality
The alternative model estimation is discussed in the next section.
6.4 Alternative structural model estimation As discussed in the previous section, an alternative model that conceptualises relationship quality as a uni-dimensional construct was estimated. As in the multi- dimensional construct model, the alternative model was estimated via the inner and outer model process.
The same methodology was employed as in the alternative model estimation process and when estimating the inner model items, factor loadings of at least 0.4 were considered significant and retained in the model (Hair et al. 2006). Thus, many of the items were not considered significant and were excluded from the analysis, particularly those related to the communication dimensions. The results of the alternative model‟s 115 outer model evaluation are exhibited in Table 6.4. As previously discussed, the internal consistency of the model was assessed via the Cronbach Alpha (Cronbach, 1970) and the composite reliability of the measurements (Werts et al., 1974). Table 6.4 illustrates that all composite reliability indices range from 0.783 to 1.00 and the Cronbach Alphas range from 0.714 to 0.943, thereby satisfying the recommended thresholds of a minimum of 0.7 for both measures (Cronbach, 1970; Werts et al. 1974).
Table 6.4: Outer model evaluation of collaborative communication dimensions, trust, satisfaction and power of alternative model.
Variables and Factor Comp Cronbach AVE indicators loading reliability
Feedback 1.000 1.000 1.000
Commfeed1 1.000
Formality 0.817 0.784 0.536
Commform1 0.545
Commform3 0.659
Commform4 0.769
Commform5 0.906
Indirect 0.783 0.714 0.651 communication
Commnews 0.937
Commsemin 0.653
Direct 0.853 0.746 0.748 communication
Comcomp 0.725
Commface 0.985
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Variables and Factor Comp Cronbach AVE indicators loading reliability
Non coercive 0.823 0.771 0.700 communication attempts
Commiflu2 0.851
Comminflu3 0.822
Relationship 0.951 0.943 0.602 Quality
Satisf1 0.858
Satisf2 0.835
Satisf3 0.622
Trust 1 0.795
Trust 2 0.831
Trust 3 0.836
Trust 4 0.782
Trust 5 0.834
Trust 6 0.773
Trust 8 0.673
Trust 9 0.791
Trust 10 0.798
Power 0.783 0.716 0.547
Power 1 0.757
Power 2 0.668
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Variables and Factor Comp Cronbach AVE indicators loading reliability
Power 3 0.789
The inner model for the alternative model was evaluated. In this step discriminant validity was observed and loadings and cross loadings matrices were examined, whereby the Pearson correlation coefficients were compared to their own constructs (Chin, 2001; Gyau & Spiller, 2007). All the loadings should be higher than the cross loadings which was the case. The results of inner model evaluation are shown in Table 6.5.
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Table 6.5: Loadings and cross loadings of indicators and constructs in the alternative model
Direct comm Formality Indirectcom Noncoercv Power RQ Wineryfeed
Commcomp 0.724857 0.176456 0.104321 0.004319 -0.063268 0.055244 -0.031968
Commface 0.985221 0.101678 -0.037266 -0.059492 -0.114375 0.222187 0.122807
Commfeed1 0.098553 0.338850 -0.009748 -0.099868 -0.329257 0.584158 1.000000
Commform1 -0.083291 0.545459 0.170199 0.071677 0.195595 0.079059 0.152243
Commform3 0.117382 0.659299 0.303213 -0.013195 0.264465 0.064982 0.131180
Commform4 0.110928 0.768881 0.279608 -0.015839 0.124804 0.164319 0.234972
Commform5 0.132427 0.906140 0.210594 -0.172532 -0.086292 0.376137 0.340996
Comminflue2 -0.062003 -0.107520 -0.086712 0.850721 0.164766 -0.162531 -0.079131
Comminflue3 -0.020207 -0.081098 0.064592 0.821803 0.102024 -0.149936 -0.088390
Commnews -0.021266 0.212307 0.936697 0.017765 0.178499 -0.068095 0.005809
Commsemin 0.019965 0.307543 0.652843 -0.083605 0.150698 -0.031477 -0.038685
Power1 -0.115950 -0.021278 0.057949 0.236038 0.757098 -0.367440 -0.226526
Power2 -0.005952 0.145729 0.182647 0.019127 0.667776 -0.249360 -0.150315
Power3 -0.098876 0.006391 0.201411 0.088106 0.788797 -0.513653 -0.309760
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Direct comm Formality Indirectcom Noncoercv Power RQ Wineryfeed
Satisf1 0.165977 0.375144 0.046365 -0.257533 -0.439535 0.850350 0.529543
Satisf2 0.143900 0.348054 0.023056 -0.214309 -0.433725 0.834888 0.536561
Satisf3 0.089546 0.242099 -0.024616 -0.251529 -0.354832 0.621710 0.335603
Trust1 0.172736 0.187600 -0.076711 -0.057324 -0.428783 0.794774 0.437217
Trust10 0.164394 0.255662 -0.078488 -0.140717 -0.428645 0.798294 0.439307
Trust2 0.175351 0.146014 -0.144919 -0.071040 -0.506581 0.830785 0.479748
Trust3 0.167048 0.232658 -0.112043 -0.142979 -0.466642 0.836326 0.530318
Trust4 0.188016 0.179914 -0.063029 -0.077604 -0.457914 0.781641 0.441711
Trust5 0.220116 0.227720 -0.139035 -0.073719 -0.447452 0.833780 0.491930
Trust6 0.144946 0.141580 -0.206856 -0.037414 -0.479143 0.772802 0.455452
Trust8 0.145447 0.242979 0.013095 -0.240236 -0.316463 0.672681 0.335300
Trust9 0.170548 0.324505 -0.006977 -0.176085 -0.409002 0.791092 0.444972
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Further discriminant validity tests were performed on the alternative model in the form of the Fornel Larcker test in which the square root of the AVE (average variance extracted) must be greater than the correlation between the construct and the other construct (Fornel & Larker, 1981; Chin, 2001). Table 6.6 illustrates the test and that the correlations between the coefficients in the model are smaller than 0.8; thereby further supporting discriminant validity (Bagozzi, 1994).
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Table 6.6: Correlations of the latent variables and the AVE square roots Direct Formality Indirectcom Noncoercv Power RQ Wineryfeed comm
Direct comm 1.0000
Formality 0.1248 1.0000
Indirect com -0.0097 0.2862 1.0000
Noncoercv -0.0501 -0.1133 -0.0168 1.0000
Power -0.1116 0.0374 0.2003 0.1609 1.0000
RQ 0.2024 0.3235 -0.0667 -0.1869 -0.5424 1.0000
Wineryfeed 0.0985 0.3388 -0.0097 -0.0998 -0.3292 0.5841 1.0000
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The structural model for the alternative model was estimated in the same fashion as the original method. The significance of the path‟s coefficients was determined using a bootstrapping method with 1000 samples. The significance was then determined by a one tail Student‟s T distribution test, at a 0.5 significance level; a T-statistic of a minimum of 1.65 would create significance at that level (Hair et al. 2006). The R2 of the model was 0.54 for the dependent variable (relationship quality) which showed a good fit for the latent construct (Chin, 2001; Gyau & Spiller, 2007). Table 6.7 illustrates the results of the structural model for the alternative model.
Table 6.7: Results of the structural model for the alternative model
Hypotheses Constructs Expected Sign Beta T-Statistic coefficients H1a Direct Com→RQ + 0.092** 2.435
H2a Indirect Com→RQ - -0.042** 1.924
H3a Feedback→RQ + 0.366** 8.163
H4a Noncoerc→RQ - -0.058** 1.747
H5a Formality→RQ - 0.209** 5.124
H6a Power→RQ - -0.402** 9.972
** Significant at p<0.05, The results shown in Table 6.7 for the alternative structural model show the confirmation of H1a, H2a, H3a, H4a and H6a and the rejection of H5a. A graphical representation of the results of the alternative structural model is shown in Figure 6.4
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Figure 6.4 Graphical representation of the alternative structural model results
** Significant at p<0.05, Solid lines represent affirmed hypotheses, dashed lines represent rejected hypotheses.
To further validate the results of the structural models, exploratory cluster analysis was performed to observe how satisfaction, power and trust were perceived by the various groups (clusters) and the demographic and contracting relations (between themselves and the wineries) of the groups. This is the area of discussion for the next section of Chapter 6.
6.5 Power, Satisfaction and Trust cluster analysis As discussed previously, an exploratory phase of the study, utilising K- Means cluster analysis, was performed to observe groups of growers and their perception of 124 satisfaction, power and trust, as the structural model indicated, and industry economic circumstance postulated, that these dimensions may be diminishing due to rising prices. In order to perform the cluster analysis the following methodology was employed.
6.5.1 Cluster analysis methodology The construct of trust was measured on eight items, satisfaction was measured on three items and power was measured on three items
SPSS statistical program version 17.0 was used for all statistical computations. Exploratory factor analysis using principal component analysis with a varimax rotation was applied to the satisfaction, power and trust constructs. In this analysis, all factors with Eigen values above one were extracted and only factors with loadings above 0.5 were retained. To test for the appropriateness of the factor analysis for the scale, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO-MSA) was conducted for all the scale items with more than one indicator variable. All fell within the accepted region of greater than 0.5 (Nunnally, 1978). In addition, these measures were purified using the Cronbach Alpha. The results of the Cronbach Alphas, factor analysis, mean, medians and standard deviation of the questionnaire items and their results are shown in Table 6.7.
Table 6.8: Factor analysis and results of Trust, Satisfaction and Power dimensions
Factors and Items Factor Mean Median Standard Loadings Deviation
Trust KMO=.909 Cronbach‟s alpha = .924, Explained variance = 60.16%
When things go bad, we believe that the 0.835 3.81 4 1.53 winery will be ready and willing to offer us assistance and support.
When making important decisions, the 0.862 3.86 4 1.63 winery is concerned about our welfare.
When we share our problems with the 0.861 3.96 4 1.52 winery we know that they will respond with understanding.
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We can count on the winery to consider 0.824 3.66 4 1.51 how its decisions and actions will affect us.
When it comes to things that are important 0.860 3.93 4 1.44 to us we can depend on the winery‟s support.
Even when the winery gives us a rather 0.798 4.13 4 1.57 unlikely explanation, we are confident that they are telling the truth.
Whenever the winery gives us advice on 0.778 4.73 5 1.35 our business operations, we know that it is sharing its best advice.
Our organisation can count on the winery 0.798 4.45 5 1.53 to be sincere.
Satisfaction KMO = .678, Cronbach„s alpha = .860, Explained variance =78.16 % We are very pleased with our working 0.907 4.80 5 1.38 relationship with the winery.
Generally we are very satisfied, with our 0.929 4.90 5 1.43 overall relationship with the winery.
RS The relationship our business has with 0.811 5.35 6 1.32 the winery has been an unhappy one.
Power KMO = .611 , Cronbach‟s alpha =.668 ., Explained variance = 61.22% We have to follow the winery‟s 0.856 5.19 6 1.58 instructions or they will get their grapes from someone else.
We are expected to follow the winery‟s 0.794 5.85 6 1.11 instructions.
The winery can, if it wanted to, severely 0.689 5.15 5 1.517 penalise us if we are uncooperative.
RS= reverse score
Hierarchical cluster analysis was performed using Ward‟s method and the resulting dendrogram uncovered three distinct clusters The respondents were then clustered into the three groups using K-Means Cluster analysis and ANOVA and cross-tab analysis was performed to see how the clusters perceived the active variables of trust,
126 satisfaction and power. The ANOVA and cross-tab analysis was also performed to see how the cluster perceived the passive variables, which related to contracting conditions, such as the length of the contract, the price per tonne paid for the grapes, length of time a respondent had worked as a grape grower, the wine region in which the grower was located and the size and ownership of the winery to which they were contracted.
F-test and Bonferroni tests were performed to see if there was a statistical difference between the clusters in terms of active and passive variables. The tests showed that the differences between some of the active and passive variables in relation to the clusters were statistically significant and all the variables that were significant within and between groups were retained (Janssens, 2008). The mean results, by cluster, are shown in Appendix 2.The cluster analysis illuminated 3 distinct relationship types and is discussed in the next section with the mean, median and standard deviation scores of the questionnaire items by cluster shown in Table 6.9. The next section of the chapter discusses the details of the cluster analysis.
Table 6.9: Questionnaire item mean, median and standard deviation score by cluster
Questionnaire item Mean Median Standard Deviation
Trust When things go bad, we believe that the winery will be ready and willing to offer us assistance and support.
Cluster 1 (n= 54) 1.83 1 1.40
Cluster 2 (n= 219) 3.66 4 1.21
Cluster 3 (n= 123) 5.86 6 1.11 When making important decisions, the winery is concerned about our welfare.
Cluster 1 (n= 54) 1.50 1 0.77
Cluster 2 (n= 219) 3.75 4 1.25
Cluster 3 (n= 123) 5.07 5 1.28 When we share our problems with the winery we know that they will respond with understanding.
Cluster 1 (n= 54) 1.67 1 0.93
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Questionnaire item Mean Median Standard Deviation
Cluster 2 (n= 219) 3.91 4 1.18
Cluster 3 (n= 123) 5.07 5 1.16 We can count on the winery to consider how its decisions and actions will affect us.
Cluster 1 (n= 54) 1.69 1 1.01
Cluster 2 (n= 219) 3.54 4 1.17
Cluster 3 (n= 123) 4.72 5 1.29 When it comes to things that are important to us we can depend on the winery‟s support.
Cluster 1 (n= 54) 1.63 1 0.81
Cluster 2 (n= 219) 3.95 4 1.02
Cluster 3 (n= 123) 4.90 5 1.14 Even when the winery gives us a rather unlikely explanation, we are confident that they are telling the truth.
Cluster 1 (n= 54) 1.78 1 1.22
Cluster 2 (n= 219) 4.15 4 1.09
Cluster 3 (n= 123) 5.15 5 1.15 Whenever the winery gives us advice on our business operations, we know that it is sharing its best advice.
Cluster 1 (n= 54) 2.61 2 1.42
Cluster 2 (n= 219) 4.82 5 0.93
Cluster 3 (n= 123) 5.51 5 0.98 Our organisation can count on the winery to be sincere.
Cluster 1 (n= 54) 2.00 2 1.16
Cluster 2 (n= 219) 4.54 5 1.11
Cluster 3 (n= 123) 5.38 6 1.12
Satisfaction
We are very pleased with our working relationship with the winery.
Cluster 1 (n= 54) 2.48 3 1.29
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Questionnaire item Mean Median Standard Deviation
Cluster 2 (n= 219) 4.76 5 0.81
Cluster 3 (n= 123) 5.88 6 0.86 Generally we are very satisfied with our overall relationship with the winery.
Cluster 1 (n= 54) 2.33 2 1.26
Cluster 2 (n= 219) 4.94 5 0.82
Cluster 3 (n= 123) 5.98 6 0.83 RS The relationship our business has with the winery has been an unhappy one.
Cluster 1 (n= 54) 3.69 4 1.97
Cluster 2 (n= 219) 5.59 6 0.88
Cluster 3 (n= 123) 6.30 6 0.66
Power
We have to follow the winery‟s instructions or they will get their grapes from someone else.
Cluster 1 (n= 54) 5.91 7 1.75
Cluster 2 (n= 219) 5.82 6 1.02
Cluster 3 (n= 123) 3.76 4 1.39 We are expected to follow the winery‟s instructions.
Cluster 1 (n= 54) 6.35 7 1.33
Cluster 2 (n= 219) 6.18 6 0.76
Cluster 3 (n= 123) 5.04 5 1.11 The winery can, if it wanted to, severely penalise us if we are uncooperative.
Cluster 1 (n= 54) 5.87 7 1.74
Cluster 2 (n= 219) 5.42 5 1.14
Cluster 3 (n= 123) 4.33 5 1.66
(RS= reverse scored)
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6.5.2 Cluster 1: “Unsustainable Relationship” Cluster 1 contained 54 respondents (14% of respondents). This group experienced strong negative power asymmetry (i.e. the winery had strong power over them) and had strong negative satisfaction and strong negative trust (strong distrust of the winery). The respondents in this group had the longest length of contract with the winery (10.5 years) and received a very low price per tonne for their grapes ($692 per tonne). This group had also spent the longest period of time as grape growers (26.69 years) and their businesses were located in warm climate wine regions (70%) such as the Riverland and Riverina. The “unsustainable relationship” involved a contract with a large, publicly owned winery (65%).
6.5.3 Cluster 2: “OK relationship” Cluster 2 contained 219 respondents (55% of respondents). This group experienced moderated negative power asymmetry (i.e. the winery had moderated negative power over them) and experienced low positive satisfaction (i.e. they were slightly satisfied with the relationship) and low negative trust. This group had the shortest length of contract (7 years) and received a medium price for their grapes ($1,264). This group had also spent the shortest period of time growing grapes (17 years) and their businesses were located in cool to warm wine growing regions such as Coonawarra, McLaren Vale, Barossa and the Yarra Valley. The “OK relationship” respondents were contracted to small to medium (70% were SME) wineries which were mostly (65%) privately owned.
6.5.4 Cluster 3: “Good Relationship” Cluster 3 contained 123 respondents (39% of respondents). This group experienced strong positive power (i.e. they had strong power over the wineries), experienced moderate satisfaction (i.e. they were moderately satisfied with the relationship), and moderate positive levels of trust (i.e. they moderately trusted the winery). Their contract with the winery was for a medium length of time in view of the other clusters (10 years) and they received the highest price for their grapes of any group ($1,981). This group had spent a medium length of time in business as grape growers compared to the other groups (19 years) and their businesses were located in cool wine growing regions (80% of this group) such as the Adelaide Hills, Barossa Valley, Yarra Valley,
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Tumbarumba, Eden Valley and Geelong. The “Good relationship” respondents were contracted to small to medium sized wineries (75% were SME) that were mostly (80%) privately owned. Table 6.10 provides a summary of the cluster analysis results. Table 6.10 provides a summary of the cluster analysis results.
Table 6.10 Summary of cluster analysis results
Unsustainable Relationship OK relationship Good relationship
54 respondents (14% of 219 respondents (55% of 123 respondents (31% of sample) sample) sample)
Grape grower experienced Grape grower Strong power asymmetry strong power asymmetry experienced moderate favouring grape grower favouring winery power asymmetry favouring winery
Grape grower experienced Grape grower Grape grower experienced strong dissatisfaction and experienced slight moderate satisfaction and strong distrust of winery satisfaction with winery trust with winery relationship and low relationship distrust
Grape grower contracted to Grape grower contracted Grape grower contracted to winery for 11 years to winery for 7 years winery for 10 years
$692 per tonne contracted $1,264 per tonne $1,981 per tonne contracted contracted
Grape grower in business for Grape grower in business Grape grower in business 27 years for 17 years for 19 years
Grape grower located in Grape grower located in Grape grower located in warm climate wine region cool to warm climate cool climate wine region wine region
Winery mainly a large, Winery mainly an SME Winery mainly an SME publicly owned business (70%), privately owned (80%), privately owned business business
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6.6 Chapter conclusion This chapter was concerned with the quantitative phase of the study. In particular it described the results of section 2 of the questionnaire instrument. Structural equation modelling illuminated the respondents‟ perceptions of communication and the effect of power, trust and satisfaction, while the cluster analysis exhibited the types of relationships that the respondents experienced. Many results have been uncovered and the discussion and implications of these results are highlighted in the next and final chapter, Chapter 7.
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Chapter 7: Discussion, conclusion and implications for further research
7.1 Chapter outline This is the final chapter of the thesis. The chapter begins with a summary of the study followed by a discussion of the hypotheses and the cluster analysis which were performed as part of the exploratory phase of the study. The research questions are discussed and the chapter ends with a discussion of the conclusion of the study and recommendations for further research. Firstly, a summary of the study is presented.
7.2 Summary of the research process The study utilised the relationship between grape grower and wineries as the research context. The justification for using this context was that:
(a) the Australian wine industry is of great economic importance to the economy of Australia; and that (b) there is a large volume of interaction between grape growers and wineries, particularly during the grape growing season, providing a fertile area for B2B research.
The study relied on the grape grower perspective of the relationship, and justification for doing so was based on the fact that:
(a) the grape grower forms the most important link in the wine production chain as the quality of the grapes they produce greatly influences the quality of the wine; and (b) the Australian wine industry is moving to focus on promotion of regionality in wine products, and regionality is grape grower based (i.e. the wine regions where the grapes are grown determines the region which is displayed on the wine bottle); (c) therefore, growing importance is being vested in the grape grower in the wine industry supply chain.
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Furthermore, there were numerous grape grower/ winery relationships with approximately 4500-6500 grape growers and 2420 wineries in the industry, and many growers had multiple relationships with multiple wineries (ABS, 2009b; Mckenzie pers. comm., May 2009; Winetitles, 2010). Potentially tens of thousands of grape grower/ winery relationships exist in the industry. The economic state of the Australian wine industry also provided the impetus for research as an oversupply of grapes had led to reduced prices for grape growers and it seemed important to explore how this phenomenon was impacting on the relationships between grape growers and wineries.
The thesis (based on the research) followed successive stages in the structural equation modelling (SEM) process. Firstly, an evaluation of the literature uncovered the dimensionality of the constructs involved in the relationship and the nature of the concept of relationship quality. Secondly, an exploratory study was performed on grape growers in South Australia and Victoria to allow for the conceptualisation (in view of the literature review) of a model and the modification of an alternative model. The exploratory study allowed for the development of hypotheses and illuminated numerous issues in the relationship between the two actors. Communication modality was of importance with face-to-face (direct) communications and non face-to-face (indirect) communication modes being highlighted by the growers. Feedback from the winery was also deemed to be important, and the issue of the formality of the communication between the two actors was of interest.
Linked to the oversupply of grape issues in the wine industry was the issue of power asymmetry, and the use of power by the wineries over the growers. Overall, the exploratory study observed that relationship quality (trust and satisfaction) was being influenced by elements of collaborative communication (as defined by Mohr & Nevin, 1990 and Mohr et al. 1996) and affected by power asymmetry. The qualitative, exploratory study allowed for the hypotheses to be formed and structural models were devised.
The structural models were then quantitatively tested (otherwise known as the causal study) on data gathered from an online questionnaire completed by 396 grape growers in South Australia, Victoria, Queensland, New South Wales, Western Australia and Tasmania (all the grape growing states in Australia). The structural models were tested utilising Partial Least Square Regression (PLS) to test the paths between constructs. The PLS SEM process utilised confirmatory factor analysis (CFA) to reduce the dimensionality of the constructs in the inner model of the structural models, and 134 regression was used to estimate the paths between constructs in the outer model of the structural models. Therefore, the SEM phase of the study tested the paths between the constructs (i.e. tested the hypotheses) and a discussion of the individual hypotheses is made in the next section of this chapter.
7.3 Hypothesis discussion The following section of this chapter provides an individual discussion of each of the hypotheses related to both the main and alternative SEM models. The discussions of the two models‟ hypotheses have been grouped together for ease of reading: that is to say, the three hypotheses related to the effect of direct modes of communication on trust, satisfaction and relationship quality have been grouped.
7.3.1 H1: Direct modes of communication positively influence trust. The PCA tests showed that the modality of communication was extracting on two components. One component was extracting on direct modes of communication and the other on indirect modes of communication. The results of the SEM showed that there was a positive, statistically significant effect of direct communication on trust. Thus, the null hypothesis is rejected and H1 is affirmed.
This result seems to affirm the findings of Cannon & Homburg (2001) and Daft & Lengel (1984); however, it focuses purely on the effectiveness of face-to-face communication and briefly on “less rich” modes of communication, without indicating what those less rich modes are. The results of the study show that email communication (that is direct to the respondent) is considered a direct mode as opposed to a group email (an email sent to a group of respondents) and has a positive effect on trust. If “rich” communication is face-to-face communication as discussed by Daft & Lengel (1984) then, in view of these results, rich communication can be more than face-to-face and, as a result, direct email communication could be considered “rich”.
7.3.2 H2: Direct modes of communication positively influence satisfaction Related to the discussion of H1, the PCA results indicate an extraction on two components and the results of the SEM showed that there is a positive link between direct communication and satisfaction. However, there was no statistically significant 135 link between direct communication and satisfaction. Therefore, the null hypothesis is accepted and H2 is rejected.
7.3.2.1 H1a: Direct modes of communication positively influence relationship quality. As previously mentioned in Chapter 6, an alternative model based on the uni- dimensional measurement of relationship quality by Leuthesser (1997) and Scheer and Stern (1992) was made. The hypothesis measured the effect that direct modes of communication had on relationship quality. The results of H1a showed a statistically significant positive effect of direct modes of communication on relationship quality. Therefore, the null hypothesis is rejected and H1a is affirmed. It appears that the uni- dimensional measure of relationship quality provides a model which better tests the effect between the two constructs, as the path between the two is statistically significant (Hair et al, 2006), as opposed to H2 which was not statistically significant.
7.3.3 H3: Indirect modes of communication negatively influence trust As discussed in the previous analysis of H1 and H2, the PCA results indicated that communication was extracting on two components. The “indirect” modes of communication were seminars and newsletters (i.e. modes that are used to communicate to a group of respondents, not individuals). The SEM process uncovered that there was a negative, statistically significant link between indirect modes of communication and trust. Therefore, the null hypothesis is rejected and H3 is affirmed. In view of the results of Cannon & Homburg (2001) and Daft & Lengel (1984) in relation to their notion of “less rich” forms of communication, newsletters and seminars must be considered “less rich”.
7.3.4 H4: Indirect modes of communication negatively influence satisfaction. The indirect modes of communication (seminar and newsletter) were hypothesised to influence satisfaction negatively. The SEM process showed that there was a positive influence of indirect modes of communication on satisfaction (opposing the hypothesis); however, the link between the two was statistically insignificant (at the 95% confidence level). Thus, the null hypothesis is accepted and H4 is rejected.
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Hypotheses 1, 2, 3 and 4 illustrated that there is a link between trust and communication modality and no link between satisfaction and communication modality. It can be surmised that no satisfaction was derived from all of the communication modes; however, there was an effect on trust. This may be the result of the wine industry economic downturn, whereby the respondents‟ levels of satisfaction are being affected by other elements of the relationship (other than communication). This quandary is discussed in later sections of this chapter.
7.3.4.1 H2a: Indirect modes of communication negatively influence relationship quality. The results of H3 showed that indirect modes of communication negatively influence trust; however, the result of H4 showed a statistically insignificant link between the construct and satisfaction. As such, the results of the main model provide a quandary in that one link between the construct and one dimension of relationship quality is significant while the other link is not. As such, the results of the alternative model whereby relationship quality is uni-dimensional are of interest.
The results of the alternative model showed a statistically significant negative link between indirect communication and relationship quality based on the Scheer & Stern (1992) and Leuthesser (1997) uni-dimensional estimation method. As such, the null hypothesis is rejected and H2a is affirmed. Therefore, the result of H2a echoes those of H3 and shows that the data provides a better fit for the model when relationship quality is measured as a uni-dimensional construct as opposed to a multi-dimensional one.
7.3.5 H5- Uni-directional communication from the winery positively influences trust As discussed in Chapter 3 (the exploratory study), the communication in the relationship was considered uni-directional (it was only coming from the wineries and not from the growers) and it was posited to be influencing trust. The SEM results showed that feedback was influencing trust statistically significantly and positively. Therefore, the null hypothesis is rejected and H5 is affirmed. This result affirms the results of the exploratory study and is in line with the results of Mohr et al. (1996);
137 however, Mohr et al. (1996) did not test the uni-dimensional nature of communication and only focused on the bi-directionality of communication which was shown to affect trust. The uni-dimensional nature of communication would appear, logically, to affect trust negatively as one actor‟s view is not being heard or acknowledged. However, the affirmation of H5 disproves this assumption.
7.3.6 H6- Uni-directional communication from the winery positively influences satisfaction. In line with the findings regarding H5, the SEM results showed that uni-directional communication (feedback) was positively, statistically, significantly influencing satisfaction, thereby affirming the results of the exploratory study and the works of Mohr et al. (1996) that feedback positively influences satisfaction. However, as in line with the discussion of H5, this is a partial fulfilment of the Mohr et al. (1996) results as that study observed the bi-directionality. Therefore, based on the results of this study, the null hypothesis is rejected and H6 is affirmed.
7.3.6.1 H3a- Uni-directional communication from the winery positively influences relationship quality. As in the estimation of H1a and H2a, H3a provided a uni-dimensional estimation of relationship quality. However, unlike the results of H2 and H4 (when estimated multi- dimensionally) the results of H5 and H6 were affirmed. In relation, to the alternative model estimation, the result of H3a affirms the multidimensional estimation in that a positive, statistical link between uni-directional communication and relationship quality was found. Therefore, the null hypothesis is rejected and H3 is affirmed. As such, the alternative model estimation mirrors the results of the main model, thereby adding weight to both models.
7.3.7 H7- Non-coercive communication attempts from the winery negatively influence trust. Mohr & Nevin (1990) posit the notion of non-coercive communication attempts and further stated that it affects the relationship but did not state if this construct directly influences trust and satisfaction. The SEM results affirm the exploratory study results
138 and showed that there was a statistically significant negative link between non-coercive communication and trust. Therefore, the null hypothesis is rejected and H7 is affirmed.
7.3.8 H8- Non-coercive communication attempts from the winery negatively influence satisfaction Connected to the discussion of H7 is the notion that non-coercive communication attempts negatively influence satisfaction. The SEM results showed that a negative link between the two constructs exists; however, the linkage was statistically insignificant. Therefore, the null hypothesis is accepted and H8 rejected.
7.3.8.1 H4a- Non-coercive communication attempts from the winery negatively influence relationship quality. Similar to the results of H2 and H4, results of the main model showed a divergence between H7 and H8 whereby H7 was affirmed and H8 was rejected. Therefore, it was of interest to observe the estimation of the alternative model whereby relationship quality was measured uni-dimensionally and, as such, H4a was observed having a uni- dimensional effect on the non-coercive construct. The results of H4a showed a statistically significant negative effect of non-coercive communication on relationship quality. Therefore, the null hypothesis is rejected and H4a is affirmed. As such, the results of H4a embody the result of H6 and show that, for this construct (non-coercive communication attempts), the alternative model, based on the uni-dimensional measurement of relationship quality, provide a better fit for the data.
7.3.9 H9- Formality of communication from the winery negatively influences trust Mohr & Nevin, (1990) and Mohr et al. (1996) commented that the formality of communication does have an effect on the relationship; however, they did not test its effect directly on trust. The exploratory study showed that it negatively influences trust, but the SEM results showed a statistically significant positive relationship between formality and trust and therefore, H9 is rejected. This is contrary to the exploratory study results and may be due to the relatively small sample size of the exploratory study interview (13). H9 was posited mainly in view of the exploratory study results, as they
139 contradicted the literature. Therefore, the SEM process has affirmed the literature and contradicted the exploratory study results.
7.3.10 H10- Formality of communication from the winery negatively influences satisfaction. In line with the literature discussion in 7.3.8, formality of communication positively influenced satisfaction. The results of the exploratory study were contradictory to this notion; therefore H10 was posited to negatively influence satisfaction. Subsequently, the SEM process showed a statistically significant positive effect of formality on satisfaction. Thus, the results of the SEM affirmed the literature, not the exploratory study and, as a result, H10 is rejected.
7.3.10.1 H5a- Formality of communication from the winery negatively influences relationship quality. The results of H9 and H10 were rejected based on the result of the main model that showed a statistically significant, positive relationship between the multi-dimensional estimation of relationship quality and the formality of communication. Similar to the results of the main model, the result of the alternative model in relation to the construct of communication formality (H5a) showed a statistically significant positive link. Therefore, the null hypothesis is accepted and H5a is rejected. As such, the main model and alternative model have shown a statistically significant negative link between the constructs.
This appears to be a confounding result, and may be because of a fault in the hypothesis generation stage of the study. The hypothesis was stated negatively based on the result of the exploratory, qualitative in-depth interviews. However, the formulation of the hypotheses was done on the basis of comments from one participant of the exploratory phase of the study which can be considered minimal and as such is listed as a limitation of the study in 7.7. Mohr et al. (1996) state that formality of communication positively influences satisfaction. In the hypothesis formulation stage of the study, the researcher was of two minds as to whether to base the hypotheses on the literature or the results of the exploratory study. The researcher decided to base the hypothesis on the findings of the exploratory study, as it would be more contextually accurate as recommended by the literature (Leedy & Ormrod, 2010). Therefore, the hypothesis would be stated in 140 terms of the context of the study (grape growers‟ opinions), as opposed to the Mohr et al. (1996) study which was performed on a generic business context.
7.3.11 H11- Power asymmetry in the relationship, favouring the winery, is decreasing growers trust in the winery. As discussed by Cox et al. (2001), Gaski, (1984) and Seyed-Mohammed & Wilson, (1990), the power asymmetry in a relationship will have a negative effect on the actor‟s (not holding the power) perception of the relationship. The discussion from wine industry literature and the exploratory study showed that there was a power asymmetry favouring the winery. The subsequent SEM process showed a statistically significant negative effect of power on growers‟ perceptions of trust in the winery. Therefore, the null hypothesis is rejected and H11 is affirmed.
7.3.12 H12- Power asymmetry in the relationship, favouring the winery, is decreasing growers‟ satisfaction with the winery. In line with the literature discussion and exploratory study results highlighted in 7.3.10, a negative influence of power asymmetry, favouring the winery, was posited. The subsequent SEM process showed a statistically significant, negative linkage between power and satisfaction; therefore, the null hypothesis is rejected and H12 is affirmed. The results relating to H11 and H12 illustrate a high power asymmetry favouring the winery and this power asymmetry is decreasing relationship quality from the growers‟ perspective.
7.3.12.1 H6a- Power asymmetry in the relationship, favouring the winery is decreasing grape growers perceptions of relationship quality. Unlike the results of previous hypotheses, for example H2 and H4, H11 and H12 were both affirmed. However, it was still of interest to observe the results of the alternative model which showed a statistically significant effect of power asymmetry decreasing grape growers‟ perceptions of relationship quality. Therefore, the null hypothesis was rejected and H6a is affirmed. As such, the results of the alternative model mirror those of the main model in relation to this construct in that power asymmetry negatively affects relationship quality.
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7.4 Cluster analysis results discussion The results of the SEM process showed, apart from other issues related to communication, that there is a strong power asymmetry favouring the winery. To observe the effect of this power asymmetry, K-means cluster analysis was performed to investigate the interaction between active variables such as power, trust and satisfaction (relationship quality) and passive variables such as the characteristics of the trading relationship between the two, and the business demographics of the growers and the wineries. This process was performed to observe if there was any commonality between the relational dimensions and aspects of the winery and grower business.
Three clusters of relationships were identified.
7.4.1 “Unsustainable Relationship” cluster Firstly, an “unsustainable relationship” cluster was observed. This cluster was associated with low relationship quality (low trust and satisfaction) and high power asymmetry favouring the winery. The elements of the trading relationship of interest were the very low price per tonne received by the grower, with an average of $692 per tonne, and a longer than average length of contract, with most of the growers located in the warm climate areas such as the Riverland and the Riverina area. This price per tonne can be considered extremely low, and below the cost of production per tonne for some growers due to increased water and other farming costs (such as fertiliser) (Stone pers. Comm., May 2010). Furthermore, this price is only slightly above the average price per tonne for grapes of the 2009 growing season, which was $529 (ABARE, 2010). It must be noted that in the questionnaire, growers were asked to focus on the most important relationship they had with a winery (noting that growers had relationships with more than one winery).
In this cluster, the most important relationship was one where the money they received would barely cover the cost of growing the grapes and, as a consequence, the growers were making only a small financial profit, or even a loss. Fourteen percent of the respondents of the whole study were therefore making a small profit or loss from their grape growing businesses, and consequently the best relationship they had (in terms of price) was financially inadequate.
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Of interest was that most of the growers in this cluster were in warm climate wine regions which are generally producers of lower quality grapes, and as a result wine, and that these regions are not the focus of recent marketing plans by the major Australian wine promotion bodies. These plans involve focusing marketing efforts on higher quality wines (AWBC, 2007) and, therefore, brings into question the overall long term viability of these regions.
Furthermore, the majority of the relationships in this cluster were with large, publicly owned wineries, and this may have power asymmetry implications. As highlighted in Chapter 5, the average respondents‟ businesses had less than three employees and, as such, have little clout in changing their business procedures; they must adapt to the wishes of the larger corporation as affirmed by Chwelos et al. 2001 and Kurokawa et al. 2008.
7.4.2 “OK relationship” cluster Secondly, a cluster of relationships termed the “OK relationship” was identified. The growers in this cluster experience less power asymmetry (i.e. possessed more power in the relationship) and higher levels of relationship quality than the “unsustainable relationship” cluster. Of great interest was the price per tonne received by this cluster, which was an average of $1264. This price was almost double that of the “unsustainable relationship” cluster and this cluster spent the shortest length of time in the relationship compared to the other clusters. This cluster had more relationships with privately owned, small to medium sized (SME) wineries compared to the “unsustainable relationship” cluster, thereby suggesting the alliance nature of two SME actors (as most respondents‟ businesses had fewer than three employees), where bonding behaviour and social bonds are built between the two parties, and each become loyal to each other (Achrol & Gundlach, 1998; Duncan & Moriarty, 1998). This is in opposition to the cultural and social distance that exists when SME and large corporations interact which can lead to a decrease in bonding behaviour (Andersen et al. 2009).
Therefore, in view of this cluster analysis, 55% of the respondents‟ best relationship was part of the “OK relationship” cluster.
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7.4.3 “Good Relationship” cluster Thirdly, a cluster of relationships termed the “Good relationship” was identified. This cluster had the highest levels of relationship quality compared to the other two clusters and, correspondingly, the power asymmetry in this cluster was lower than was the case with the other two clusters. Therefore, respondents in this cluster possessed the most power in relationships compared to the other clusters. This cluster received the highest average price per tonne of any of the clusters ($1981) and the members of this cluster were primarily located in cool growing regions. The members of this cluster had relationships with more SME wineries than any of the other clusters.
7.4.4 Questionnaire item results discussion, by cluster The results of the questionnaire item, particularly the mean scores of the items, were of interest in relation to the scores given by each cluster. There were a number of great discrepancies between the mean results, and the most notable are discussed.
The questionnaire item “Trust 1” had a mean score of 1.83 for the “Unsustainable Relationship” cluster, and 3.66 and 5.89 for the “OK Relationship” and “Good Relationship” clusters, respectively. The questionnaire item read that “when things go bad, we believe the winery will offer us support and assistance”. Therefore, the “Unsustainable Relationship” cluster believed that they would be offered minimal support when things went bad, with the other two clusters receiving more support, and the “Good Relationship” cluster receiving the most support. This result shows that the relationships that have higher levels of relationship quality receive more assistance and support during difficult times.
Questionnaire item “Trust 2” had a mean score of 1.50 for the “Unsustainable Relationship” cluster, and 3.25 and 5.03 for the “OK Relationship” and “Good Relationship” clusters, respectively. The questionnaire item read that “when making important decisions, the winery is concerned about the respondent‟s welfare”. Therefore, the “Unsustainable Relationship” cluster believed that the winery had little concern for their welfare when making decisions, with the “OK Relationship” and “Good Relationship” cluster believing that the winery was more concerned with their welfare, with the “Good Relationship” cluster receiving the most care. The result was that this questionnaire item showed that respondents who experienced a higher level of
144 relationship quality had relationships with wineries that were concerned about their welfare when making decisions.
The questionnaire item “Trust 6” had a mean score of 1.78 for the “Unsustainable Relationship” cluster, and 4.18 and 5.15 for the “OK Relationship” and “Good Relationship” clusters, respectively. The questionnaire item read that when wineries offered an unlikely explanation, the respondents believed that the winery was telling the truth. In view of the results, the “Unsustainable Relationship” cluster believed that the winery was lying (i.e. not telling the truth) when giving an explanation, with the “OK Relationship” and “Good Relationship” clusters believing that the winery was telling more of the truth, and the “Good Relationship” cluster experiencing the most truthful responses when given an explanation. Therefore, respondents that had relationships higher in relationship quality involved wineries that told more truth when giving explanations.
Questionnaire item “Power 1” had a mean score of 5.91 for the “Unsustainable Relationship” cluster, and 5.87 and 3.76 for the “OK Relationship” and “Good Relationship” clusters, respectively. The questionnaire item read that the respondents had to follow the winery‟s instructions or they would get their grapes from somewhere else, with a higher mean score illustrating the respondent had to follow the winery‟s instructions or be discarded, and vice versa. Therefore, the “Unsustainable Relationship” had to follow the winery‟s instructions or be discarded; this was less of a requirement for the “OK Relationship” and was the least for the „Good Relationship” cluster. Thus, respondents who had relationships that contained higher levels of relationship quality had greater power in the relationship and consequently feared less the possibility of being discarded if they did not follow the winery‟s directions explicitly. It appeared that respondents who did experience higher levels of relationship quality could set their own agendas, to a certain degree, and possibly be more able to use their own initiative when growing their grapes.
Questionnaire item “Power 4” had a mean score of 5.82 for the “Unsustainable Relationship” cluster, and 5.42 and 4.33 for the “OK Relationship” and “Good Relationship” clusters, respectively. The item read that if the winery wanted to, it could severely punish the respondent if he/she was uncooperative. Therefore, it appeared that the “Unsustainable Relationship” cluster could be highly punished. The “OK Relationship” and “Good Relationship” cluster were likely to be punished to a lesser degree, with the “Good Relationship” cluster likely to be punished least if they were 145 uncooperative. The results showed that respondents who had relationships with a higher level of relationship quality would be punished the least if they were uncooperative.
7.4.5 Cluster results summary The cluster analysis illuminated some interesting features regarding the relationships between grape growers and wineries and the effect these relationships have on relationship quality and the influence of power asymmetry. The influence of growing region, price per tonne and the size of the winery on relationship quality and power asymmetry was also of interest. In view of the cluster analysis findings, for a grape grower to attain higher levels of relationship quality and power in the relationships they must:
1. be located in a cooler climate wine region; 2. have short relationships with wineries; and 3. deal with SME wineries.
In view of this study‟s results, if grape growers achieved these three objectives, they would potentially attain higher prices for their grapes.
Furthermore, taking into account the mean score of questionnaire items by cluster that showed high discrepancies between means, respondents who experienced relationships that contained a higher level of relationship quality:
1. received more support from the winery during difficult times; 2. had wineries who were more concerned for the respondents‟ welfare when making decisions; 3. were involved wineries that told more of the truth; 4. were allowed to work more without having to follow explicit instructions; 5. had a reduced fear of retribution for not following instructions; and 6. experienced less punishment if they were uncooperative.
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7.5 Research Question Summary Three research questions were devised for this study. The following sections of this chapter discuss the research questions, incorporating how the questions were answered.
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7.5.1 Question 1: Which relational constructs constitute relationship quality? The concept of relationship quality has been widely discussed in marketing literature. However, there was much conjecture as to the antecedents of relationship quality and no specific consensus has been reached by the various authors. A detailed analysis of the literature in Chapter 2 revealed that relationships that are high in trust and satisfaction are high in relationship quality. Therefore, this research question was answered by stating that the relational constructs of trust and satisfaction led to relationship quality. The study also examined two perspectives of relationship quality, namely a multi-dimensional and uni-dimensional perspective. Both perspectives conceptualise that relationship quality is comprised of trust and satisfaction; however, in the multi-dimensional conceptualisation, proposed by Crosby (1990), Dorch (1998) and Kim et al. (2006), relationship quality is perceived as two separate constructs (trust and satisfaction ). If a relationship is high in those two constructs, it is high in relationship quality. This perspective of relationship quality was examined in the main SEM model. The study also examined the uni-dimensional nature of relationship quality, proposed by Stern & Scheer (1992) and Leuthesser (1997), and is tested in the alternative SEM model, by which relationship quality is measured as a single construct with latent variables consisting of trust and satisfaction.
7.5.2 Question 2: Which elements of the grape grower/ winemaker relationship affect grape growers‟ perceptions of relationship quality? The exploratory study, highlighted in Chapter 3, involved qualitative interviews with grape growers. The purpose of those interviews was to identify the factors in the relationship that affected relationship quality, and to provide weight to the construction of the conceptual model. The interviews uncovered that communication was important, particularly the dimensionality of communication, and had an effect on relationship quality. Furthermore, the construct of power also affected the relationship. The quantitative phase of the study tested the relationship between these elements and observed the effect between them. In combining the effect that the communication elements and power had on trust and satisfaction (in the SEM process), the following observations were made.
1. Direct communication positively influences relationship quality. 2. Indirect communication negatively influences relationship quality. 3. Uni-directional communication positively influences relationship quality. 147
4. Non-coercive communication attempts negatively influence relationship quality. 5. Formality of communication positively influences relationship quality. 6. Power asymmetry negatively influences relationship quality
The notion of power asymmetry favouring the winery is particularly evident in the study and can be shown in the SEM models presented in Chapter 6. In both the main and alternative models, the beta coefficient of the regression analysis (the affect dimension) between the construct of power asymmetry and relationship quality has the strongest effect in the model. In the main model, the beta coefficient for the paths between power asymmetry and trust and satisfaction are the strongest in the main model with -0.402 and -0.341, while the same is true in the alternative model with a beta coefficient of -0.402 between power asymmetry and relationship quality. As such, in both models the effect of power asymmetry is the strongest of all affects. This result quantitatively shows that power asymmetry is a major factor in the relationships between grape growers and wineries in the Australian wine industry.
7.5.3 Question 3: Are there any commonalities between wine grape growers in their perceptions of relationship quality? K- Means cluster analysis was performed in the quantitative phase of the study to observe if there were any commonalities between grape growers in their perception of relationship quality. Commonalities were found, mainly based on the nature of the trading relationships with wineries, the regions in which the grape growers were located, and the size and ownership of the wineries that growers were trading with. The main commonalities were that:
1. Grape growers in cooler climate wine regions experienced higher levels of relationship quality. 2. Grape growers who traded with smaller sized wineries experienced higher levels of relationship quality. 3. Grape growers who traded with privately owned wineries, as opposed to publicly owned wineries, experienced higher levels of relationship quality. 4. Grape growers who received a higher price per tonne for their grapes experienced higher levels of relationship quality. 5. Grape growers who had shorter contracts with wineries experienced higher levels of relationship quality.
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7.6 Conclusion The wine industry is important to the economy of Australia. Not only does the industry generate vast sums of income from domestic and export sales, but it employs tens of thousands of people directly and indirectly through allied industries that support the wine industry.
The industry is currently suffering economic hardship, mainly due to an oversupply of grapes, and relationships between grape growers and winemakers have become adversarial, resulting in a break down in the relationship between the two actors. The industry may return to a sustainable level of grape supply and, if this occurs, the relationship between the two actors must become fruitful in order to produce wine fit for the market.
Furthermore, the wine industry is restructuring its grape production abilities to concentrate on the production of higher quality wine, and to emphasise the regionality of wine products in marketing efforts, particularly in export markets. Quality of wine and regionality of wine products is grape grower derived; therefore, the grape grower plays a vital role in the future prosperity of the wine industry. As such, the grape grower perspective of the relationship between the two actors is of importance.
This study attempted to ascertain the relational factors that are of importance to the grape grower and that affect relationship quality .The exploratory study highlighted that the dimensionality of communication and the power asymmetry in the relationship, favouring the winery, was influencing relationship quality. The results of the causal study highlighted that face-to-face and direct email communication positively affected relationship quality, while non-direct modes (such as seminars and newsletters) negatively affected relationship quality and that the power asymmetry was leading to decreased grape prices and lower relationship quality. It appeared that the price of the grape growers‟ produce (grape) had a direct correlation with relationship quality, whereby the higher the price they received, the higher the level of relationship quality they experienced. Further analysis as part of the causal study highlighted the effect that the size and ownership of the winery had on relationship quality, with growers dealing with larger, publicly owned wineries experiencing lower levels of relationship quality. Grape growers that had their businesses in warmer climate regions, as opposed to cooler climate regions, also experienced lower levels of relationship quality.
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If the Australian wine industry is to find prosperity in the future, it must invest in the relationships between grape growers and wineries by focusing on the needs and wants of the actor that has the greatest impact on the core quality of the end product, so that the end product is fit for market. This study attempted to uncover these needs and wants via a multistage research process, which is illustrated in pages of this dissertation.
7.7 Study Limitations This study has various limitations associated with the sample of respondents and the scope of the study. As previously discussed in Chapter 3, the exploratory, qualitative study contained 13 respondents for the in-depth interviews. This number is small and the respondents were only from two states of Australia (South Australia and Victoria), and it can be posited that they are not representative of grape growers Australia wide. Furthermore, respondents in the qualitative phase of the study were not located in the two largest respondent localities in the quantitative phase of the study. These two areas were the Riverland and Riverina wine regions. As a result, data was not obtained in the qualitative research phase from these regions and is, therefore, a limitation of the study.
The causal, quantitative study involved the responses of 396 grape growers from all states of Australia; however, not all wine regions in Australia had respondents contained in the 396 and, therefore, that presents a limitation. The respondents were asked to answer the questionnaire items in view of their most important relationship. A limitation of the study is that not all of the relationships that respondents had with wineries were recorded. Respondents had an average of two other relationships with wineries, as shown in Chapter 5; however, limitations in regard to time and length of response related to respondent fatigue, made this so. In addition, the formulation H, in regards to formality of communication, was based on the comments of two IDI participants and it was later found in the causal stages of the research that an opposite effect was observed (negative as opposed to positive effect on relationship quality).
The formulation of the hypothesis was flawed due to the small number of responses (2) and as such is a limitation of the study. In comparison, the formulation of H7 and H8 was based on one comment from a participant; however, the hypotheses were affirmed. In any case, developing the hypotheses on one response is a limitation of the study.
The questionnaire was distributed via an online mode, as it was deemed cost effective in administration and could be accessed by respondents, as expert opinions suggested 150 that respondents had access to internet services. However, the rural nature of the respondents does suggest that some potential respondents would not be able to complete the survey due to sporadic internet connections, or having no internet connection at all. Therefore, a different mode of survey administration, such as paper- based, mail administration or face to face administration, may have led to more valid responses.
The SEM process of this study utilised Partial Least Squares Regression to estimate the paths between constructs. This method was used due to the small number of indicator variables for certain constructs (i.e. less than three for certain constructs). However, this method was subject to some criticisms for not being as robust as other methods such as those employed by AMOS or LISREL, which use maximum differences to test paths (Chin, 1998; Hair et al. 2006; Ringle et al. 2005), and as such can be considered a limitation of this study. Also, the latent variables for certain constructs, particularly “satisfaction”, are small in number (fewer than four for a dependent variable), and as such may be providing an AVE (average variance extracted) that is small and this may account for the statistically insignificant results shown in H2, H4 and H8. The Cronbach Alpha for each latent variable is passable (Cronbach, 1970); however, the small number of variables may have led to the insignificant results and as such is a limitation of the study (Hair et al, 2006; Ringle, 2005). If the dependent variable of “satisfaction” contained more reliable latent variables in terms of higher AVE‟s and Cronbach alphas, the results of H2, H4 and H8 may have been significant.
Cluster analysis was performed in the final phase of the study to uncover the types of relationships that grape growers had with wineries. The analysis showed types of relationships; however, the number of responses that made up the cluster (396 responses) is small for cluster analysis purposes. Even though cluster analysis is an exploratory research method (Janssens et al. 2008), it is usually performed on larger sample sizes in order to gain robust results. However, ANOVA results performed on the passive variables in the cluster analysis showed statistically significant differences between the clusters and therefore the clusters were sound. Nevertheless, the smaller sample size utilised in the cluster analysis is a limitation of the study.
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7.8 Recommendations for further research The results of this study have highlighted a number of areas for further research. This study primarily focused on the grape grower perspective of communication dimensionality, power and relationship quality in regards to the relationship between themselves and their buyers (the wineries). While justification was given for this, the winery‟s perspective is also important to view, and further research could test the constructs highlighted in this study on wineries. A model incorporating both perspectives of the relationship could then be attained.
The respondents of this study were asked to answer questionnaire items in relation to the most important relationship that they had with wineries. Further research could be performed investigating all the relationships that growers had with wineries and SEM could be performed examining the differences between those relationships and the way that the constructs examined in this study differ between relationships. The results of the study have shown an interaction between price, power and satisfaction, whereby price of product (in this study, grapes) moderates the effect that power asymmetry has on satisfaction. This moderating effect could be examined in further research.
The study uncovered the effects that the size and the ownership of the winery had on relationship quality. It was shown that, when dealing with small to medium sized, privately owned wineries, growers experienced less power asymmetry (they had more power in the relationship) and relationship quality was higher. It appeared that buyer size and ownership moderated the effect that power had on relationship quality, and this concept requires further investigation.
The interaction of elements of the relationship between the two (for example, price per tonne of grapes, length of the relationship, size and ownership of the winery, wine region of the grower) and relational constructs (e.g. satisfaction, power, trust) was observed in this study. However, further research could be performed, investigating how grower-specific characteristics affect the relational constructs such as the type of grape (red or white) or variety of grape (for example, Chardonnay, Riesling, Shiraz) that is produced by the grape growers or how the yield per acre of the grapes produced has an effect or mediates an effect between relational variables. This investigation would be of interest as it is known that certain varieties are renowned in certain wine regions (for example, Coonawarra is known for Cabernet Sauvignon production), and if growers produce grapes that are renowned in a region, do they experience less power asymmetry and higher levels of relationship quality (Domine, 2000)? 152
The study focused on the interaction between price per tonne and power asymmetry; however, it did not consider the interaction between yield of grapes per acre and power asymmetry. It is known that lower yield per acre creates a higher quality of grapes (Domine, 2000) but if grape growers produce lower yield (higher quality grapes) as opposed to higher priced grapes, do they experience a higher level of relationship quality and lower power asymmetry? Therefore, the concept that if yield per acre increases, power asymmetry increases, requires further investigation.
Further analysis of questionnaire items illuminated a number of areas for future research, particularly how demonstrative aspects of trust and power asymmetry affect relationship quality. For example, future research could focus on the effect that a partner‟s assistance during difficult economic times has on the other partner‟s perceptions of relationship quality. Furthermore, a business‟ concern for the welfare of their partner when making decisions, and its effect on relationship quality perceptions of the partner, could be observed. The effect of dishonesty on partner relationship quality perception could also be observed. In relation to power asymmetry, the effect of partner initiative on power asymmetry, observed in addition to the effect that power asymmetry has on the level of punishment used by the business, could be examined.
7.9 Study contribution This study has provided a contribution to both academic marketing and Australian wine industry literature. Firstly, the study has provided an insight into communication in B2B relationships and shows that communication can be direct or indirect and focused on specific modes. The study further examined Mohr & Nevin‟s (1990) concept of collaborative communication, and provided an extension of this theory, but focussing on modality and uni-directionality. The study also highlighted the effect of power asymmetry on relationship quality. This study also aided the Australian wine industry by highlighting the state of various grape grower and winery relationships, by providing clusters of relationships, and by providing various industry statistics such as grape grower and winery business details (e.g., place of business, size). As mentioned in 1.5, this study attempted to extend Hobley‟s (2007) work by further investigating the effect that communication (and its elements) and power asymmetry had on the relationship between the two actors. The study differed from Hobley (2007) by focusing on individual communication elements (whereas Hobley, 2007 focused on communication as a single construct), and power asymmetry and its overall effect on relationship 153 quality. Finally, a major contribution of the study was to show the effect that lowering grape prices is having on grape growers‟ perceptions of relationship quality.
This study has also added to the knowledge of communication in an agribusiness context by applying the Mohr & Nevin (1990) and Mohr et al, 1996 collaborative communication framework to the context, and has as such extended parts of Storer‟s (2005) inter-organisational information management systems (IOIMS) by examining different elements of communication and their effects on agribusiness relationships such as computer based modes and the formality and non-coercive abilities of communication. As such, the study has added to Storer‟s (2005) work by examining communication between business actors in an agribusiness context.
This study differs from other studies that have observed the relationship between grape growers and wineries (such as Scales et al. (1995), Anderson, 2001 and Hobley, 2007), by observing the concept of relationship quality, in particular, the effect that the price of grapes and communication elements have on relationship quality. The study has also contributed to knowledge by quantitatively observing the relationships in the wine industry, which is different from studies by Benson-Rea (2005) and Rampersad (2008) which were mainly qualitative in nature. Furthermore, the study satisfied a need for research into communication between grape growers and wineries as proposed by Spawton & Walters (2003), Chong (2007) and Brown (2008), and showed that communication from the grape grower to the winery is limited and uni-directional, and that direct forms of communication such as face-to-face and personal email communication have better effects than indirect forms such as seminars and newsletters. These results appear to highlight what is discussed in the academic literature, such as that by Daft & Lengel (1984), which shows that personal or rich forms of communication have better outcomes, and add to their work by highlighting the effect of electronic communication forms, such as emails or communications on the internet, which were not examined by Daft & Lengel (1984) due to those forms of communication not being present in the past.
This study also stands out from these other studies by quantitatively testing the effect of power asymmetry on the relationship between the two actors. However, the other studies were performed when grape oversupply was not as prevalent and therefore not justified. The study has shown that the Australian wine industry grape grower and winery relationship is different in terms of power asymmetry from other wine industries where the power asymmetry is favouring the grape grower. This is evident in the 154
Champagne region where, due to a limited number of grape growers, they have a power asymmetry over the Champagne houses (wineries) (Charters & Menival, 2010). This study also illustrated three types of grape grower relationships with wineries based on relationship quality and power asymmetry, a contribution that has not been provided before.
7.10 Study implications for the Australian wine industry This study has provided a number of implications for Australian winery and grape grower interactions. The main proposition to come from this study is that direct communication (for example face-to-face and direct email modes) should be used by wineries when interacting with grape growers instead of indirect communication (seminars and newsletter modes). Lowered grape prices are also affecting grape growers; however, this can be linked to issues outside of the control of the wineries and may not be able to be changed by wineries. Nevertheless, the study has shown that wineries can control their behaviour and need to be more truthful, give more support to grape growers during these difficult times, and show concern for their grape growers when making decisions. By recognising that these issues exist, wineries will improve their relationships with grape growers, and therefore the sustainability of the Australian wine industry. The results of the study could also aid policy makers in the Australian wine industry. The study highlighted three types of relationships, of which one was unsustainable. By taking note of the business characteristics of the unsustainable relationship group, policy makers could target these businesses and give them the necessary support to encourage them to leave the industry.
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Appendix 1: Questionnaire
In regards to your most important winery business relationship
How many years have you been contracted to the winery (number of years)
Approximately how many tonnes of grapes do you supply to the winery (number of tonnes)
Approximately what is the dollar amount of those grapes ($)
What is your average price per tonne of grapes you supply to the winery ($)
Do you sell your grapes to other wineries? If so, how many other wineries (number of wineries)
What proportion (%) of your grapes do you sell to the other wineries(%)
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For each of the following methods, over the 2009 Vintage growing season (August 08- May 09), please estimate the frequency (the number of times) with which the winery communicates with you via these various methods.
Please type in the "number of times" as a number, e.g. "4" rather than "four". If you did not communicate via a certain method, please put "0"
Face to face interaction with winery people (number of times) (Required)
Telephone interaction (telephone calls) with winery people (number of times) (Required)
Written letters and all written correspondence (non-electronic e.g. no email) (number of times) (Required)
Direct Email, from a wine representative to you(number of times) (Required)
Seminars [e.g. Grower Days (winery - growers meetings)] (number of times) (Required)
General newsletters from the winery (number of times) (Required)
Other (number of times)
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The next few questions relate to the formality of communication between you and the winery. When you liaise with the winery, there are formal and informal methods of communication. For example, if communication is formal it is done on a regular basis and is written down, whereas informal communication is generally verbal (in words) and not done on a regular basis.
Please indicate how strongly you agree on the following statements Strongly Disagree 1 Strongly Agree 2 3 4 5 6 7 When working with this winery, formal communication channels are followed (i.e. communication is formal, regular and structured) versus casual informal, word –of-mouth modes). The terms of our business contract with the winery have been written down in detail. The winery‟s expectations of us are communicated in detail.
The terms of our business relationship with the winery have been explicitly put into words and discussed. Information sharing on important issues has become crucial to maintaining this partnership. We share a common, specialised IT software system dedicated to facilitate communication with the winery (e.g. Vine Access®). Grower liaison committees, that communicate my issues and concerns with the large wineries, are effective.
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The next few questions are regarding the feedback that the winery provides to you and vice versa.
Please indicate by clicking the box that corresponds with your answer None A lot 1 2 3 4 5 6 7 How much positive feedback do you provide to this winery?
How much negative feedback do you provide to this winery?
How much negative feedback does this winery provide to you?
How much positive feedback does this winery provide to you?
In their interaction with you, the winery often tries to influence YOUR attitudes and behaviours. Please estimate the frequency with which the winery‟s employees (e.g. winemakers, grower liaison staff, viticultural staff) use the following methods to influence YOU.
Very Very infrequently frequently 1 2 3 4 5 6 7 How frequently did the winery‟s employees make a recommendation that by following their suggestions, your business would be more profitable. How frequently did the winery‟s employees ask you to perform a certain operation, but didn‟t say what penalty may occur if you didn‟t do what they asked. How frequently did the winery‟s employees say you will be supplying grapes of a certain quality, but didn‟t give you specific information e.g. what crop level they would like, what spray regime they would like or other directions they would like you to take to
159 grow those grapes.
The following question are about trust in your business relationship with the winery. Please indicate how strongly you agree with the following statements: Strongly Strongly Disagree Agree 1 2 3 4 5 6 7 When things go bad, we believe that the winery will be ready and willing to offer us assistance and support. When making important decisions, the winery is concerned about our welfare. When we share our problems with the winery we know that they will respond with understanding. We can count on the winery to consider how its decisions and actions will affect us.
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Strongly Strongly Disagree Agree 1 2 3 4 5 6 7 When it comes to things that are important to us we can depend on the winery‟s support. Even when the winery gives us a rather unlikely explanation, we are confident that they are telling the truth. The winery has often provided us information that has later proven to be incorrect. The winery keeps the promises that it makes to our business.
Whenever the winery gives us advice on our business operations, we know that it is sharing its best advice. Our organisation can count on the winery to be sincere.
The following questions are about how satisfied you are with the business relationship you have with the winery.
Please indicate how strongly you agree with the following statements: Strongly Strongly Disagree Agree 1 2 3 4 5 6 7 We are very pleased with our working relationship with the winery.
Generally we are very satisfied, with our overall relationship with the winery. The relationship our business has with the winery has been an unhappy one.
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The following questions are about power in the relationship. By power we mean the ability to influence another person‟s actions.
Please indicate how strongly you agree with the following statements: Strongly Strongly Disagree Agree 1 2 3 4 5 6 7 We have to follow the winery‟s instructions or they will get their grapes from someone else. We are expected to follow the winery‟s instructions.
We have influence over the winery‟s actions.
The winery can, if it wanted to, severely penalise us if we are uncooperative. If we did not want to follow the winery‟s instructions or plans we could sell our grapes to another winery.
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We would like to find out some details regarding you, your business and the winery.
Please rest assured that all information is kept strictly confidential and is not passed onto any organisation. No one is named in person or identified in anyway
If you are asked to give a number e.g. 5 acres, type in "5" rather than "five" Please list the size in acres of your vineyards (number of acres) (Required)
How many years have you been growing grape vines (number of years) (Required)
How many people work for your grape growing business (number of people) (Required)
Please indicate which wine region you are located in (Required) Wine Region
Do you have any formal grape growing qualifications? If so list
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In what wine region is the winery that you supply grapes to (i.e. the winery you have focussed on and discussed in the survey) (Required) Wine Region
Is the winery (that you have focussed on and discussed in this survey)Click on the box (Required)
In your opinion is the size of the winery (Click on box) (Required)
Thank you for completing this survey! To be in the running to win $2000 worth of Viticultural services from Davidson Viticulture, please enter your name (including business name), address and phone details below.
Please take note that all of your details are kept in strictest confidence. Your details will not be handed on to anyone
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Appendix 2: Cluster Analysis Results
165
Descriptive statistics of active variables, by cluster
95% Confidence Interval for Mean Between- Component N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum Variance Trust Unsustainable Relationship 54 -1.7757443 .65463284 .08908425 -1.9544247 -1.5970639 -2.59249 .29294 OK Relationship 219 -.0261752 .56347996 .03807645 -.1012203 .0488699 -1.90935 1.27316 Good Relationship 123 .8261997 .63169695 .05695820 .7134453 .9389542 -.65120 2.40560
Total 396 .0000000 1.00000000 .05025189 -.0987946 .0987946 -2.59249 2.40560 Model Fixed Effects .59815865 .03005860 -.0590958 .0590958 Random Effects .68302098 -2.9388021 2.9388021 1.10619863 Satisfaction Unsustainable Relationship 54 -1.8519137 .85781989 .11673450 -2.0860534 -1.6177739 -3.29015 -.15743 OK Relationship 219 .0080012 .51075600 .03451369 -.0600220 .0760245 -1.38496 1.58266 Good Relationship 123 .7987891 .53894408 .04859495 .7025906 .8949877 -.85374 1.58266 Total 396 .0000000 1.00000000 .05025189 -.0987946 .0987946 -3.29015 1.58266 Model Fixed Effects .57802539 .02904687 -.0571067 .0571067 Random Effects .69543275 -2.9922056 2.9922056 1.14698810 Power Unsustainable Relationship 54 .5858628 1.26153005 .17167250 .2415314 .9301943 -4.14183 1.43853 OK Relationship 219 .3817124 .58615600 .03960875 .3036473 .4597775 -1.51639 1.43853 Good Relationship 123 -.9368423 .79627588 .07179778 -1.0789732 -.7947114 -4.14183 .60245 Total 396 .0000000 1.00000000 .05025189 -.0987946 .0987946 -4.14183 1.43853 Model Fixed Effects .77591317 .03899110 -.0766572 .0766572
Random Effects .53856240 -2.3172470 2.3172470 .68548296
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ANOVA results of active variables, by cluster
Sum of Squares df Mean Square F Sig. Trust Between Groups (Combined) 254.387 2 127.194 355.494 .000 Linear Term Unweighted 254.051 1 254.051 710.050 .000 Weighted 236.465 1 236.465 660.896 .000
Deviation 17.922 1 17.922 50.091 .000 Within Groups 140.613 393 .358 Total 395.000 395 Satisfaction Between Groups (Combined) 263.693 2 131.847 394.617 .000 Linear Term Unweighted 263.662 1 263.662 789.140 .000 Weighted 238.244 1 238.244 713.063 .000 Deviation 25.450 1 25.450 76.171 .000 Within Groups 131.307 393 .334 Total 395.000 395 Power Between Groups (Combined) 158.398 2 79.199 131.551 .000 Linear Term Unweighted 87.008 1 87.008 144.521 .000 Weighted 130.747 1 130.747 217.173 .000 Deviation 27.651 1 27.651 45.929 .000
Within Groups 236.602 393 .602 Total 395.000 395
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Bonferroni Test on active variables, by cluster
Dependent Variable (I) Power Sat Trust (J) Power Sat Trust Mean 95% Confidence Interval Cluster 3 Cluster 3 Difference (I-J) Std. Error Sig. Lower Bound Upper Bound Trust Cluster 1 Cluster 2 -1.74956909* .09088219 .000 -1.9680746 -1.5310635
dimension3 Cluster3 -2.60194404* .09764580 .000 -2.8367112 -2.3671769 Cluster 2 Cluster 1 1.74956909* .09088219 .000 1.5310635 1.9680746
dimension2 dimension3 Cluster3 -.85237495* .06739921 .000 -1.0144210 -.6903289 Cluster3 Cluster 1 2.60194404* .09764580 .000 2.3671769 2.8367112
dimension3 Cluster 2 .85237495* .06739921 .000 .6903289 1.0144210 Satisfaction Cluster 1 Cluster 2 -1.85991490* .08782321 .000 -2.0710658 -1.6487640
dimension3 Cluster3 -2.65070280* .09435917 .000 -2.8775680 -2.4238376
Cluster 2 Cluster 1 1.85991490* .08782321 .000 1.6487640 2.0710658
dimension1 dimension2 dimension3 Cluster3 -.79078791* .06513064 .000 -.9473797 -.6341961 Cluster3 Cluster 1 2.65070280* .09435917 .000 2.4238376 2.8775680
dimension3 Cluster 2 .79078791* .06513064 .000 .6341961 .9473797 Power Cluster 1 Cluster 2 .20415048 .11788960 .012 -.0792883 .4875892
dimension3 Cluster3 1.52270512* .12666316 .000 1.2181724 1.8272379
Cluster 2 Cluster 1 -.20415048 .11788960 .012 -.4875892 .0792883
dimension2 dimension3 Cluster3 1.31855464* .08742821 .000 1.1083534 1.5287559 Cluster3 Cluster 1 -1.52270512* .12666316 .000 -1.8272379 -1.2181724
dimension3 Cluster 2 -1.31855464* .08742821 .000 -1.5287559 -1.1083534 Cluster 1= Unsustainable Relationship, Cluster 2= OK Relationship, Cluster 3= Good Relationship
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Descriptive statistics of passive variables, by cluster
95% Confidence Interval for Mean Between- Component N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum Variance How many Cluster 1 54 10.50 10.062 1.369 7.75 13.25 0 56 years Cluster 2 219 7.18 6.830 .461 6.27 8.09 0 70 contracted Cluster3 123 9.98 9.604 .866 8.26 11.69 0 60 Total 396 8.50 8.367 .420 7.68 9.33 0 70 Model Fixed Effects 8.256 .415 7.69 9.32 Random 1.228 3.22 13.79 3.173
Effects Average price Cluster 1 54 $692.69 $453.003 $61.646 $569.04 $816.33 $100 $2,000 per tonne Cluster 2 219 $1,264.91 $681.833 $46.074 $1,174.11 $1,355.72 $0 $4,000 Cluster3 123 $1,981.32 $1,097.062 $98.919 $1,785.50 $2,177.14 $250 $7,000 Total 396 $1,409.40 $916.237 $46.043 $1,318.88 $1,499.92 $0 $7,000 Model Fixed Effects $811.896 $40.799 $1,329.19 $1,489.61 Random $363.864 $-156.18 $2,974.98 $310,591.4
Effects 92 Years have Cluster 1 54 26.69 23.946 3.259 20.15 33.22 4 168 you been Cluster 2 219 17.81 11.549 .780 16.27 19.35 3 100 growing grape Cluster3 123 19.37 10.303 .929 17.53 21.21 3 50 vines Total 396 19.51 13.856 .696 18.14 20.88 3 168 Model Fixed Effects 13.575 .682 18.17 20.85 Random 2.460 8.92 30.09 13.277
Effects 169
Descriptive statistics of passive variables, by cluster
95% Confidence Interval for Mean Between- Component N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum Variance How many Cluster 1 54 10.50 10.062 1.369 7.75 13.25 0 56 years Cluster 2 219 7.18 6.830 .461 6.27 8.09 0 70 contracted Cluster3 123 9.98 9.604 .866 8.26 11.69 0 60
Total 396 8.50 8.367 .420 7.68 9.33 0 70 Model Fixed Effects 8.256 .415 7.69 9.32 Random 1.228 3.22 13.79 3.173
Effects Average price Cluster 1 54 $692.69 $453.003 $61.646 $569.04 $816.33 $100 $2,000 per tonne Cluster 2 219 $1,264.91 $681.833 $46.074 $1,174.11 $1,355.72 $0 $4,000 Cluster3 123 $1,981.32 $1,097.062 $98.919 $1,785.50 $2,177.14 $250 $7,000 Total 396 $1,409.40 $916.237 $46.043 $1,318.88 $1,499.92 $0 $7,000 Model Fixed Effects $811.896 $40.799 $1,329.19 $1,489.61 Random $363.864 $-156.18 $2,974.98 $310,591.4
Effects 92 Years have Cluster 1 54 26.69 23.946 3.259 20.15 33.22 4 168 you been Cluster 2 219 17.81 11.549 .780 16.27 19.35 3 100 growing grape Cluster3 123 19.37 10.303 .929 17.53 21.21 3 50 vines Total 396 19.51 13.856 .696 18.14 20.88 3 168 Model Fixed Effects 13.575 .682 18.17 20.85 Random 2.460 8.92 30.09 13.277
Effects Cluster 1= Unsustainable Relationship, Cluster 2= OK Relationship, Cluster 3= Good Relationship
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ANOVA results of passive variables
Sum of Squares df Mean Square F Sig. How many years contracted Between Groups 863.877 2 431.938 6.337 .002 Within Groups 26786.621 393 68.159 Total 27650.497 395 Average price per tonne Between Groups 7.254E7 2 3.627E7 55.025 .000 Within Groups 2.591E8 393 659175.592 Total 3.316E8 395 Years have you been Between Groups 3413.208 2 1706.604 9.261 .000 growing grape vines Within Groups 72419.769 393 184.274 Total 75832.977 395
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Bonferroni Test on passive variables, by cluster Bonferroni
Dependent Variable (I) Power Sat Trust (J) Power Sat Trust Mean 95% Confidence Interval Cluster 3 Cluster 3 Difference (I-J) Std. Error Sig. Lower Bound Upper Bound How many years contracted Cluster 1 Cluster 2 3.317* 1.254 .026 .30 6.33
dimension3 Cluster3 .524 1.348 .032 -2.72 3.76 Cluster 2 Cluster 1 -3.317* 1.254 .026 -6.33 -.30
dimension2 dimension3 Cluster3 -2.793* .930 .009 -5.03 -.56
Cluster3 Cluster 1 -.524 1.348 .032 -3.76 2.72
dimension3 Cluster 2 2.793* .930 .009 .56 5.03 Average price per tonne Cluster 1 Cluster 2 $-572.228* $123.357 .000 $-868.81 $-275.64
dimension3 Cluster3 $-1,288.632* $132.537 .000 $-1,607.29 $-969.98 Cluster 2 Cluster 1 $572.228* $123.357 .000 $275.64 $868.81
dimension2 dimension3 Cluster3 $-716.404* $91.483 .000 $-936.35 $-496.45 Cluster3 Cluster 1 $1,288.632* $132.537 .000 $969.98 $1,607.29
dimension3 Cluster 2 $716.404* $91.483 .000 $496.45 $936.35 Years have you been Cluster 1 Cluster 2 8.872* 2.063 .000 3.91 13.83
dimension3 growing grape vines Cluster3 7.311* 2.216 .003 1.98 12.64 Cluster 2 Cluster 1 -8.872* 2.063 .000 -13.83 -3.91
dimension2 dimension3 Cluster3 -1.561 1.530 .024 -5.24 2.12 Cluster3 Cluster 1 -7.311* 2.216 .003 -12.64 -1.98
dimension3 Cluster 2 1.561 1.530 .024 -2.12 5.24
*. The mean difference is significant at the 0.05 level.
172
Climate of Growers‟ wine region, by cluster
Cool Cool Cool Cool Cool Cool Don’t Warm Warm Warm Warm NSW QLD SA Tas Vic WA know NSW SA Vic WA TOTAL Cluster 1 1 0 17 0 1 2 0 13 18 0 2 54 Cluster 2 13 5 64 4 31 10 24 31 27 6 4 219 Cluster3 8 1 56 2 22 8 1 16 5 2 2 123 Total 22 6 137 6 54 20 25 60 50 8 8 396
Wine Region of Grower, by cluster
Cluster 1= Unsustainable Relationship, Cluster 2= OK Relationship, Cluster 3= Good Relationship. 173
Ownership of winery, by cluster
C r o Chi-Square Test of winery, by cluster test s Asymp. Sig. (2- s Value df sided) t Pearson Chi-Square 27.511a 2 .000 a Likelihood Ratio 26.895 2 .000 b Linear-by-Linear 24.920 1 .000 C Association o N of Valid Cases 365
u a. 0 cells (.0%) have expected count less than 5. The minimum expected count is
n 17.26. t
174
Appendix 3: IDI discussion questions 1. Is communication important in your relationship with wineries?
PROMPT: Are there any types or modes of communication that you like?
PROMPT: What is the feedback from the winery like?
PROMPT: Do you have any other comments about the communication you have with wineries?
2. How has the economic down turn in the industry affected your business?
PROMPT: Has it affected your relationship with wineries?
PROMPT: How?
3. Any other issues you would like to discuss about your winery relationships?
4. How is the vintage going?
PROMPT: Any water issues?
PROMPT: Any frost problems?
PROMPT: How is the drought effecting growing?
175
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