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: [email protected]

Kei-Teng Chang College of Management and Economics Kunming University of Science and Technology E-mail: [email protected]

Wan-Chun Duan College of Management and Economics Kunming University of Science and Technology E-mail: [email protected]

Kuei-Lun Chang Graduate Institute of Industrial and Business Management National Taipei University of Technology E-mail: [email protected] 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-Chun Duan 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.

2 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

3 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 Literatures

C1: Profit The profitability of new Cebeci (2009); Liao and Chang program. (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 Eilat, Golany, and Shtub (2008); audience. 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).

4 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 Cebeci (2009); Chen, Huang, and employee. 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 Learning Priority business and growth weights process

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

5 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.

MostMost optimaloptimal newnew programprogram projectproject

FinancialFinancial CustomerCustomer InternalInternal businessbusiness processprocess LearningLearning andand growthgrowth processprocess

C : Profit C : Audience C : Lead time C : Well-being 1 5 9 13

C : Cost C : Brand C : Risk C : Capability 2 6 10 14

C : Budget C : New audience C : New technology C : Training 3 7 11 15

C : New market C : Market C : Facility C : Satisfaction 4 8 12 16

ProjectProject 11 ProjectProject 22 ProjectProject 33

Figure 1. Hierarchy for new program projects selecting.

Table 3. The pairwise comparisons within Financial perspective. Profit Cost Budget New Priority market weights

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 Market Priority audience weights

6 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 Facility Priority technology weights

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 Priority weights

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 3

C1 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

7 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 3

C1 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.

8 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. The hierarchy proposed in this paper considers 16 critical criteria. We suggest that future research studies can incorporate more criteria in order to conduct more accurate estimates. Additionally, AHP assumes that factors in the hierarchy are independent. Considering the interdependent relation among factors, another decision making approach, analytic network process (ANP), can be applied to handle such problems. Moreover, AHP ignores the fuzziness of executives’ judgment during the decision-making process. We suggest that follow-up researchers could analyze this topic with the concept of fuzzy sets.

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