New Program Projects Selecting for TV Companies
New program projects selecting for TV companies
Sen-Kuei Liao
Department of Business Management
National Taipei University of Technology
E-mail:
Kei-Teng Chang
College of Management and Economics
Kunming University of Science and Technology
E-mail:
Wan-ChunDuan
College of Management and Economics
Kunming University of Science and Technology
E-mail:
Kuei-Lun Chang
Graduate Institute of Industrial and Business Management
National Taipei University of Technology
E-mail:
New program projects selecting for TV companies
Sen-Kuei Liao
Department of Business Management
National Taipei University of Technology
Kei-Teng Chang
College of Management and Economics
Kunming University of Science and Technology
Wan-ChunDuan
College of Management and Economics
Kunming University of Science and Technology
Kuei-Lun Chang
Graduate Institute of Industrial and Business Management
National Taipei University of Technology
Abstract
Selecting new program projects plays an important role for TV companies. Balanced scorecard (BSC) which links financial and non-financial, tangible and intangible, inward and outward factors can provide an integrated viewpoint for decision makers to select optimal new program projects. This study combines BSC with analytic hierarchy process (AHP) to help Taiwanese TV company managers make better decisions in new program projects selection. Moreover, the practical application of the proposed approach is generic and also suitable to be exploited for Taiwanese TV companies.
Keywords: Analytic hierarchy process; Balanced scorecard; TV industry
Introduction
New product development (NPD) is one of the key to get competitive advantage and maintain growth of the firm (Chang and Cho, 2008; Liao, Hsieh, and Huang, 2008; Wang, 2009). However, NPD is a risky process (Ozer, 2005). Less than 15% of NPD projects are commercially successful (Cooper, 2001). As the result, the vital issue in NPD is how to evaluate the future success of new products (Balachandra, 1984; Benson, Sage, and Cook, 1993). In Taiwanese TV industry, the product is its program. The rating would be influenced by programs. The amount and fees of advertising obtained by TV companies would be affected by the rating. The TV companies depend largely on advertising to maintain their operation. In other words, evaluating and selecting new program projects plays an important role for TV companies.
Nevertheless, most of the evaluation approaches merely focus on the effect of financial benefit, quality, possible amount of potential customers and so on (Oh, Suh, Hong, and Hwang, 2009). The decision makers need a comprehensive evaluation model for the future success of new program projects. BSC proposed by Kaplan and Norton (1992) is widely applied to evaluate business performance. BSC links financial and non-financial, tangible and intangible, inward and outward factors can provide an integrated viewpoint for decision makers to evaluate the new program projects. AHP, proposed by Saaty in the 1970’s, allows factors to be compared, with the importance of individual factors being relative to their effect on the problem solution (Saaty, 1980). AHP has been widely applied for decision-making problems. We combines BSC with AHP to help Taiwanese TV company managers make better decisions for new program projects selection.
In this paper, we firstly present BSC. Next, AHP as selection tools is described. The proposed approach within the context of selecting the optimal new program projects is shown in Section 4. The conclusion is given in Section 5.
Balanced scorecard (BSC)
BSC proposed by Kaplan and Norton (1992) is widely applied to evaluate business performance. BSC is with the intent to keep score of a set of measures that maintain a balance between financial and non-financial measures, between internal and external performance perspectives. Of the BSC 4 perspectives, one is financial and the other 3 involve non-financial performance measurement indexes: customer, internal business process and learning and growth. The financial perspective is about how the strategic action contributes to the improvement of revenue. In customer perspective, customers are the source of business profits. Hence, satisfying customer needs is the objective pursued by companies. The objective of internal business process perspective is to satisfy shareholders and customers by excelling at business processes. The goal of the last perspective, learning and growth, is to provide the infrastructure for achieving the objectives of the other 3 perspectives and for creating long-term growth and improvement through systems, employees and organizational procedures (Kaplan and Norton, 1996).
Method: Analytic hierarchy process (AHP)
AHP, proposed by Saaty in the 1970’s, is designed to structure a decision process in a scenario affected by independent factors (Saaty, 1980). AHP allows factors to be compared, with the importance of individual factors being relative to their effect on the problem solution. Priorities are established using pairwise comparisons. The weight assigned to each perspective and criterion may be estimated from the data or subjectively by decision makers. It would be desirable to measure the consistency of the decision makers’ judgment. AHP provides a measure through the consistency ratio (C.R.) which is an indicator of the reliability of the model. This ratio is designed in such a way that the values of the ratio exceeding 0.1 indicate inconsistent judgment.
Application
The sample company consists of a family of 4 major channels and own almost 900 staff. There are 3 new program projects in the case study. The decision committee includes 3 managers. We depict AHP selecting process as follow.
Step 1. Hierarchy construction and problem structuring
Reviewing literatures about BSC, we collect criteria for new program projects selection of Taiwanese TV companies. The Likert 9 point scale questionnaires based on criteria of BSC are sent to 48 executives to obtain the importance of criteria for selecting the new program projects. According to the geometric mean values, we choose top 4 criteria under each perspective to structure the hierarchy for new program projects selecting, as shown in Figure 1.
Table 1. Definitions and literatures of selecting criteria.
Criteria / Definition / LiteraturesC1: Profit / The profitability of new program. / Cebeci (2009); Liao and Chang (2010).
C2: Cost / The cost of new program. / Lee, Chen, and Chang (2008); Chen, Huang, and Cheng (2009); Liao and Chang (2009a); Liao and Chang (2009b); Tseng (2010).
C3: Budget / Budget management. / Liao and Chang (2009a); Liao and Chang (2009b); Liao and Chang (2010).
C4: New market / New market expansion. / Hubbard (2009).
C5: Audience / The satisfaction index of audience. / Eilat, Golany, and Shtub (2008); Lee, Chen, and Chang (2008); Chen, Huang, and Cheng (2009); Liao and Chang (2009a); Liao and Chang (2009b); Wu, Tzeng, and Chen (2009); Liao and Chang (2010); Tseng (2010); Yüksel and Dağdeviren (2010).
C6: Brand / The reputation of brand. / Cebeci (2009); Liao and Chang (2009a).
C7: New audience / New audience acquisition. / Chang, Tung, Huang, and Yang (2008); Chen, Huang, and Cheng (2009); Hubbard (2009); Wu, Tzeng, and Chen (2009); Tseng (2010); Yüksel and Dağdeviren (2010).
C8: Market / Market sharing. / Chang, Tung, Huang, and Yang (2008); Chen, Huang, and Cheng (2009); Hubbard (2009); Wu, Tzeng, and Chen (2009); Liao and Chang (2010); Tseng (2010); Yüksel and Dağdeviren (2010).
C9: Lead time / Lead time of new program. / Cebeci (2009); Chen, Huang, and Cheng (2009); Hubbard (2009); Tseng (2010).
C10: Risk / Risk minimization. / Chen, Huang, and Cheng (2009); Liao and Chang (2009a).
C11: New technology / New technology adoption. / Yüksel and Dağdeviren (2010).
C12: Facility / Facility utilization. / Cebeci (2009); Hubbard (2009); Liao and Chang (2009b); Tseng (2010).
C13: Well-being / Employee well-being. / McPhail, Herington, and Guilding (2008).
C14: Capability / The capability of employee. / McPhail, Herington, and Guilding (2008); Tseng (2010); Yüksel and Dağdeviren (2010).
C15: Training / Employee training. / Lee, Chen, and Chang (2008); Cebeci (2009); Chen, Huang, and Cheng (2009); Hubbard (2009); Liao and Chang (2009b); Wu, Tzeng, and Chen (2009); Yüksel and Dağdeviren (2010).
C16: Satisfaction / The satisfaction index of employee. / Cebeci (2009); Chen, Huang, and Cheng (2009); Liao and Chang (2009a); Liao and Chang (2009b); Wu, Tzeng, and Chen (2009); Liao and Chang (2010); Tseng (2010); Yüksel and Dağdeviren (2010).
Table 2. The pairwise comparisons and priority weights of perspectives.
Financial / Customer / Internal business process / Learning and growth / Priorityweights
λmax＝4.0877 C.R.＝0.0295
Financial / 1.0000 / 1.4422 / 3.1072 / 1.2599 / 0.3703
Customer / 0.6934 / 1.0000 / 1.0000 / 1.2599 / 0.2322
Internal business process / 0.3218 / 1.0000 / 1.0000 / 0.7937 / 0.1708
Learning and growth / 0.7937 / 0.7937 / 1.2599 / 1.0000 / 0.2267
Step 2. Determine the perspectives and criteria weights
A series of pairwise comparisons made by a decision committee are applied to establish the relative importance of perspectives. In these comparisons, a 1-9 scale is applied to compare 2 perspectives. The pairwise comparison matrix and the development of each perspective priority weight are shown in Table 2. Subsequently, we apply pairwise comparisons again to establish the criteria weights within each perspective, showing in Table 3 to 6.
Figure 1. Hierarchy for new program projects selecting.
Table 3. The pairwise comparisons within Financial perspective.
Profit / Cost / Budget / New market / Priorityweights
λmax＝4.0554 C.R.＝0.0187
Profit / 1.0000 / 2.1544 / 3.9149 / 1.0000 / 0.3759
Cost / 0.4642 / 1.0000 / 1.0000 / 0.5503 / 0.1568
Budget / 0.2554 / 1.0000 / 1.0000 / 0.2752 / 0.1136
New market / 1.0000 / 1.8171 / 3.6342 / 1.0000 / 0.3536
Table 4. The pairwise comparisons within Customer perspective.
Audience / Brand / New audience / Market / Priorityweights
λmax＝4.0271 C.R.＝0.0091
Audience / 1.0000 / 1.3572 / 4.6416 / 3.9791 / 0.4595
Brand / 0.7368 / 1.0000 / 2.2680 / 3.5569 / 0.3206
New audience / 0.2154 / 0.4409 / 1.0000 / 1.0000 / 0.1140
Market / 0.2513 / 0.2811 / 1.0000 / 1.0000 / 0.1059
Table 5. The pairwise comparisons within Internal business process perspective.
Lead time / Risk / New technology / Facility / Priorityweights
λmax＝4.0989 C.R.＝0.0333
Lead time / 1.0000 / 1.8171 / 4.8203 / 5.2415 / 0.4901
Risk / 0.5503 / 1.0000 / 4.6416 / 3.6342 / 0.3287
New technology / 0.2075 / 0.2154 / 1.0000 / 0.4368 / 0.0704
Facility / 0.1908 / 0.2752 / 2.2894 / 1.0000 / 0.1109
Table 6. The pairwise comparisons within Learning and growth perspective.
Well-being / Capability / Training / Satisfaction / Priorityweights
λmax＝4.1435 C.R.＝0.0483
Well-being / 1.0000 / 1.4422 / 2.4101 / 3.6342 / 0.4136
Capability / 0.6934 / 1.0000 / 2.7144 / 2.2894 / 0.3161
Training / 0.4149 / 0.3684 / 1.0000 / 0.4368 / 0.1115
Satisfaction / 0.2752 / 0.4368 / 2.2894 / 1.0000 / 0.1589
Table 7. The weight of each alternative with respect to criteria.
Project 1 / Project 2 / Project 3C1 / 0.4366 / 0.2500 / 0.3134
C2 / 0.4145 / 0.2618 / 0.3237
C3 / 0.4718 / 0.2886 / 0.2396
C4 / 0.5769 / 0.1973 / 0.2258
C5 / 0.2995 / 0.3503 / 0.3503
C6 / 0.1907 / 0.2932 / 0.5161
C7 / 0.3244 / 0.2693 / 0.4063
C8 / 0.1989 / 0.2962 / 0.5049
C9 / 0.4416 / 0.2391 / 0.3193
C10 / 0.3689 / 0.2633 / 0.3678
C11 / 0.5324 / 0.1228 / 0.3447
C12 / 0.3034 / 0.5412 / 0.1554
C13 / 0.6027 / 0.2554 / 0.1418
C14 / 0.4630 / 0.2435 / 0.2935
C15 / 0.4967 / 0.1979 / 0.3054
C16 / 0.6494 / 0.2054 / 0.1452
Step 3. Determine the composite weights of AHP
The weight of each alternative with respect to the criteria is shown in Table 7. According to Table 2 to 7, we can aggregate the composite weights of AHP shown in Table 8.
Step 4. Final decision making
According to Table 8, the ranking is Project 1, Project 3, and Project 2. We provide the result to the case company for consultation. The case company executes Project 1, according to our conclusion.
Conclusion
NPD is one of the key to get competitive advantage. However, NPD is a risky and complicated process. The vital issue in NPD is how to evaluate the future success of new products. In Taiwanese TV industry, the product is its program. The TV companies depend largely on advertising to maintain their operation. The amount and fees of advertising obtained by TV companies would be affected by the rating. The rating would be influenced by programs. In other words, evaluating and selecting new program projects plays an important role for TV companies. The decision makers need a comprehensive evaluation model for the future success of new program projects. BSC links financial and non-financial, tangible and intangible, inward and outward factors can provide an integrated viewpoint for decision makers to evaluate the new program projects. AHP, proposed by Saaty in the 1970’s, has been widely applied for decision-making problems. We combines BSC with AHP to help Taiwanese TV company managers make better decisions for new program projects selection.
Table 8. The composite weights of AHP.
Project 1 / Project 2 / Project 3C1 / 0.0608 / 0.0348 / 0.0436
C2 / 0.0241 / 0.0152 / 0.0188
C3 / 0.0198 / 0.0121 / 0.0101
C4 / 0.0755 / 0.0258 / 0.0296
C5 / 0.0320 / 0.0374 / 0.0374
C6 / 0.0142 / 0.0218 / 0.0384
C7 / 0.0086 / 0.0071 / 0.0108
C8 / 0.0049 / 0.0073 / 0.0124
C9 / 0.0370 / 0.0200 / 0.0267
C10 / 0.0207 / 0.0148 / 0.0206
C11 / 0.0064 / 0.0015 / 0.0041
C12 / 0.0057 / 0.0103 / 0.0029
C13 / 0.0565 / 0.0239 / 0.0133
C14 / 0.0332 / 0.0174 / 0.0210
C15 / 0.0126 / 0.0050 / 0.0077
C16 / 0.0234 / 0.0074 / 0.0052
Composite weights / 0.4353 / 0.2619 / 0.3028
In this paper, we firstly review literatures about BSC to collect the selecting criteria. The Likert 9 point scale questionnaires based on criteria of BSC are sent to 48 executives to obtain the importance of criteria for selecting new program projects. According to the geometric mean values, we choose top 4 criteria under each perspective including: Profit, Cost, Budget, New market, Audience, Brand, New audience, Market, Lead time, Risk, New technology, Facility, Well-being, Capability, Training, Satisfaction to structure the hierarchy for new program projects selecting.
We employed specialized EXCEL software to process the data provided by the decision makers to derive the optimal alternative. In this paper, we find that the C.R. of each pairwise comparison was less than 0.1, which means that the reliability of data was accepted. Moreover, a practical application to select new program projects presented in Section 4 is generic and also suitable to be exploited for Taiwanese TV companies.