博碩士論文 108423063 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:12 、訪客IP:3.145.40.121
姓名 王佳倫(Jia-Lun Wang)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 商業智慧管理能力在提高決策績效中的作用
(Role of Business Intelligence Management Capability in Enhancing Decision-Making Performance)
相關論文
★ 影響ERP導入過程及成效因素之研究 - 單一公司兩次導入SAP系統之比較分析★ 運用資料倉儲技術建置物力動員資訊系統之開發
★ 買方採用自有電子市集之個案研究─以台塑企業為例★ DEA模型評估經營效率之研究—以某綜合證券商為例
★ 尋求卓越:中小企業資訊部門的管理之個案研究★ 「證券商共同網路交易平台」之可行性分析
★ 產業競合模式策略探討-以自行車產業為例★ RFID導入航空貨運站出口作業流程應用之研究
★ 綠色供應鏈活動建構之個案研究-以筆記型電腦製造業為例★ 導入資訊科技服務管理之評估-以遠東銀行為例
★ 資訊系統導入歷程中專案團隊決策衝突之探討★ 應用資源基礎理論探討持久競爭優勢-以智慧型手機H公司為例
★ 服務導向架構為基礎的企業流程管理之探討 - 以瀚宇博德股份有限公司為例★ 沙賓法案實施與企業遵循個案研究--以K公司為例
★ 資訊服務委外之個案分析-以銀行簡訊為例★ 有線電視業者經營IPTV之競爭優勢分析—以個案公司為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 隨著科學技術的進步,全球化已成為世界趨勢,這意味著資訊傳播速度更快,企業每天所需要接收的資訊量也在增加。為了更快地理解數據,企業開始使用商業智慧(BI)系統來探索這些數據,以便管理和使用所有可用的資訊。企業之所以要導入BI系統最主要的目的便是協助企業制定決策,並藉此提高決策績效。良好的決策績效能幫助企業更快地回應客戶的需求且更早地制定計劃,從而提高業務流程績效。因此,對於資訊主管來說,如何更好地使用BI系統以及在使用BI系統時該注意哪些層面便成了重要的議題。
在本研究中,我們認為要讓BI系統取得成功,除了需要良好的管理能力,還要人力資源和基礎架構等資源。因此,我們提出了一個模型用以衡量BI管理能力、BI技術基礎建設質量、BI人員專業知識、決策績效及業務流程績效之間的影響。我們利用問卷的方式蒐集了台灣前1237大製造業的資料來驗證我們的假說是否成立。最後,本研究提供一個較為系統的角度來了解如何透過BI系統來提升業務流程績效。
摘要(英) With the advancement of technology and science, globalization has become a world trend, which means that information spreads faster, and the amount of information that firms need daily is also increasing. In order to utilize the data more effectively, firms began to use business intelligence (BI) systems to explore data in order to manage and use all available information. The main reason why firms want to introduce BI systems is to help firms make better decisions, thus improving decision-making performance. Good decision-making performance can assist firms respond to customer needs faster and develop plans faster, thereby improving business process performance. Therefore, for IT managers, how and when to use BI system properly has become an important issue.
This study holds that in order for a BI system to succeed, in addition to good management capabilities, resources such as human resource and infrastructure are also required. Therefore, we propose a model to examine the relationships among BI management capabilities, BI technical infrastructure, BI personnel expertise, decision-making performance, and business process performance. We collected data from the top 1,237 manufacturing firms in Taiwan with a survey to examine the measures of the constructs and test the hypotheses. This research thus provides a more systematic perspective to understand how to improve business process performance through BI systems. Implications of the results are provided.
關鍵字(中) ★ 商業智慧管理能力
★ 商業智慧科技基礎建設質量
★ 商業智慧人員專業技術
★ 決策績效
★ 業務流程績效
關鍵字(英) ★ BI Management Capability
★ BI Technical Infrastructure Quality
★ BI Personnel Expertise
★ Decision-Making Performance
★ Business Process Performance
論文目次 摘要 i
Abstract ii
誌謝 iii
Contents iv
List of Figures vi
List of Tables vii
1. Introduction 1
1.1 Research Background and Motivations 1
1.2 Research Objectives and Questions 5
2. Literature Review 6
2.1 BI Management Capability 6
2.2 BI Personnel Expertise 8
2.3 BI Technical Infrastructure Quality 10
2.4 Decision-Making Performance 12
2.5 Business Process Performance 13
3. Research Model and Hypotheses 15
3.1 Research Framework 15
3.2 BI Management Capability and BI Personnel Expertise 16
3.3 BI Management Capability and BI Technical Infrastructure Quality 17
3.4 BI Management Capability and Decision-Making Performance 18
3.5 BI Personnel Expertise and Decision-Making Performance 19
3.6 BI Technical Infrastructure Quality and Decision-Making Performance 20
3.7 Decision-Making Performance and Business Process Performance 21
4. Research Methodology 22
4.1 Sample Selection and Data Collection 22
4.2 Operationalization of Constructs 23
4.2.1 BI Management Capability 25
4.2.2 BI Personnel Expertise 26
4.2.3 BI Technical Infrastructure Quality 28
4.2.4 Decision-Making Performance 30
4.2.5 Business Process Performance 30
4.3 Control Variables 32
4.4 Research Procedures 32
5. Data Analysis and Results 33
5.1 Respondent Characteristics 33
5.2 Measurement Model 38
5.2.1 Examination of Second-Order Constructs 38
5.2.2 Reliability and Validity 43
5.2.3 Common Method Bias 47
5.3 Structural Model 48
5.3.1 PLS Results of Hypotheses Testing 48
5.3.2 Robustness Analysis 49
6. Conclusions 52
6.1 Findings and Discussions 52
6.2 Research Implications 54
6.3 Limitations 55
References 56
Appendix Questionnaire 62
參考文獻 Acharya, A., Singh, S. K., Pereira, V., and Singh, P. (2018). Big data, knowledge co-creation and decision making in fashion industry. International Journal of Information Management, 42, 90–101.
Anand, A., Fosso, W. S., and Sharma, R. (2013). The effects of firm IT capabilities on firm performance: The mediating effects of process improvement. ACIS 2013 Proceedings, 17.
Aringhieri, R., Carello, G., and Morale, D. (2016). Supporting decision making to improve the performance of an Italian emergency medical service. Annals of Operations Research, 236(1), 131–148.
Aydiner, A. S., Tatoglu, E., Bayraktar, E., and Zaim, S. (2019). Information system capabilities and firm performance: Opening the black box through decision-making performance and business-process performance. International Journal of Information Management, 47, 168–182.
Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., and Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of Business Research, 96, 228–237.
Baars, H., and Kemper, H. G. (2008). Management support with structured and unstructured data - an integrated Business intelligence framework. Information Systems Management, 25(2), 132–148.
Banker, R. D., Bardhan, I. R., Chang, H., and Lin, S. (2006). Plant information systems, manufacturing capabilities, and plant performance. MIS Quarterly, 30(2), 315–337.
Baum, J. R., and Wally, S. (2003). Strategic decision speed and firm performance. Strategic Management Journal, 24(11), 1107–1129.
Bernhard, W., Peter, B., Zoltan, M. P., and Maria-Luise, O. (2006). The impact of ERP systems on firm and business process performance. Journal of Enterprise Information Management, 19(1), 13–29.
Bharadwaj, A. S. A. (2000). Resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169-196.
Bhatt, G. D., and Grover, V. (2005). Types of information technology capabilities and their role in competitive advantage: An empirical research. Journal of Management Information Systems, 22(2), 253–277.
Bisogno, S., Calabrese, A., Gastaldi, M., and Ghiron, N. L. (2016). Combining modelling and simulation approaches. How to measure performance of business processes? Business Process Management Journal, 22(1), 56–74.
Boar, B. (1996). Cost effective strategies for client/server systems. New York: John Wiley & Sons.
Boynton, A., Zmud, R. W., and Jacobs, G. C. (1994). The influence of IT management practice on IT use in large organizations. MIS Quarterly, 18(3), 299–318.
Bradford, M., and Florin, J. (2003). Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems. International Journal of Accounting Information Systems, 4(3), 205–225.
Byrd, T. A., and Turner, D. E. (2000). Measuring the flexibility of information technology infrastructure: Exploratory analysis of a construct. Journal of Management Information Systems, 17(1), 167–208.
Cepeda, C. G., Cegarra, N. J. G., and Jimenez, J. D. (2012). The effects of absorptive capacity on innovativeness: Context and information systems capability as catalysts. British Journal of Management, 23(1), 110–129.
Chen, H. C., Chiang, R. H. L., and Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188.
Chin, W. W. (1998). The partial least squares approach for structural equation modeling, in modern methods for business research. George A. Marcoulides (ed.), Lawrence Erlbaum Associates, New York, pp. 295–336.
Chin, W. W., Marcolin, B. L., and Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14 (2), pp. 189–217.
Clark, T. D., and Jones, M. C. (2008). An experimental analysis of the dynamic structure and behavior of managerial support systems. System Dynamics Review, 24(2), pp. 215–245.
Clark, T. D., Jones, M. C., and Armstrong, C. P. (2007). The dynamic structure of management support systems: Theory development, research focus, and direction. MIS Quarterly, 31(3), pp. 579–615.
Conway, J. M., and Lance, C. E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25, 325–334.
Curtis, M. B., and Joshi, K. (1998). Lessons learned from the implementation of a data warehouse. Journal of Data Warehousing, 3(2), pp. 12–18.
Davenport, T. H., and Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business Press.
Davenport, T. H. (2010). Business intelligence and organizational decisions. International Journal of Business Intelligence Research, 1(1), 1–12.
Dehning, B., and Richardson, V. J. (2002). Returns on investments in information technology: A research synthesis. Journal of Information Systems, 16(1), 7–30.
Dinter, B. (2013). Success factors for information logistics strategy – An empirical investigation. Decision Support Systems, 54(3), pp. 1207–1218.
Elbashir, M. Z., Collier, P. A., and Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135–153.
Evelson, B., McNabb, K., Karel, R., and Barnett, J. (2007). It’s time to reinvent your BI strategy, Retrieved on February 2012 from Forrester Research, http://www.forrester.com/Research/Document/Excerpt/0,7211,43259,00.html.
Gartner, I. (2013). Gartner predicts business intelligence and analytics will remain top focus for CIOs through 2017. [Press release]. Retrieved from https://www.gartner.com/newsroom/id/2637615.
Gartner, I. (2016). Gartner says worldwide business intelligence and analytics market to reach $16.9 Billion in 2016, http://www.gartner.com/newsroom/id/3198917.
Hattie, J. (1985). Methodology review: Assessing unidimensionality of tests and items. Applied Psychological Measurement, 9, 139–164.
Helfat C., Finkelstein S., Mitchell W., Peteraf M. A., Singh H, Teece D. J., and Winter S. G. (2007). Dynamic capabilities: Understanding strategic change in organizations. Blackwell: Oxford, U.K.
Hou, C. K. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: an empirical study of Taiwan′s electronics industry. International Journal of Information Management, 32(6), 560–573.
Isik, O., Jones, M. C., and Sidorova, A. (2013). Business intelligence success: The roles of BI capabilities and decision environments. Information and Management, 50(1), pp. 13–23.
James, D. W., and Mark, S. P. (1996). Does decision process matter? A study of strategic decision-making effectiveness. The Academy of Management Journal, 39(2), 368–396.
Jones, G. K., Lanctot, A., and Teegen, H. J. (2001). Determinant and performance impact of external technology acquisition. Journal of Business Venturing, 16, 255–283.
Kaltoft, M., Cunich, M., Salkeld, G., and Dowie, J. (2014). Assessing decision quality in patientcentred care requires a preference-sensitive measure. The Journal of Health Services Research & Policy, 19(2), 110–117.
Karimi, J., Somers, T. M., and Gupta, Y. P. (2001). Impact of information technology management practices on customer service. Journal of Management Information Systems, 17(4), 125–158.
Kim, G., Shin, B., Kim, K. K., and Lee, H. G. (2011). IT capabilities, process-oriented dynamic capabilities, and firm financial performance. Journal of the Association for Information Systems, 12(7), 487.
Kiron, D., Shockley, R., Kruschwitz, N., Finch, G., and Haydock, M. (2011). Analytics: The widening divide. MIT Sloan Management Review, (Nov), pp. 1–22.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10.
Kowalczyk, M., Buxmann, P., and Besier, J. (2013). Investigating business intelligence and analytics from a decision process perspective: A structured literature review. Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
Larson, D., and Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700–710.
Laursen, G. H., and Thorlund, J. (2017). Business analytics for managers: Taking business intelligence beyond reporting(2nd ed.). Hoboken, NJ, USA: John Wiley & Sons.
Lavalle, S., Lesser, E., Shockley, R., Hopkins, M. S., and Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21–32.
Lee, D. M. S., Trauth, E., and Farwell, D. (1995). Critical skills and knowledge requirements of IS professionals: A joint academic/industry investigation. MIS Quarterly, 19(3), 313–340.
Lowry, P. B., and Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, (57:2), pp. 123–146.
Luo, J., Fan, M., and Zhang, H. (2012). Information technology and organizational capabilities: A longitudinal study of the apparel industry. Decision Support Systems, 53(1), 186–194.
Marcoulides, G.A., and Saunders, C.(2006). PLS: a silver bullet? MIS Quarterly, 30(2), pp. iii–x.
McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D., and Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60–68.
McKenna, J. P. (2011). Moving toward Real-Time Data Warehousing. Business Intelligence Journal, 16(3), 14-19.
Melville, N., Kraemer, K., and Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322.
Mithas, S., Lee, M. R., Earley, S., Murugesan, S., and Djavanshir, R. (2013). Leveraging big data and Business Analytics [guest editors’ introduction]. IT Professional, 15(6), 18–20.
Najjar, M. S. and Kettinger, W. J. (2013). Data Montetization: Lessons From a Retailer’s Journey. MIS Quarterly Executive, 12(4), pp. 213–225.
Nevo, S., and Wade, M. (2011). Firm-level benefits of IT-enabled resources: a conceptual extension and an empirical assessment. Journal of Strategic Information Systems, 2, 403–418.
Peppard, J. (2007). The conundrum of IT management. European Journal of Information Systems, 16(4), 336–345.
Pérez-López, S., and Alegre, J. (2012). Information technology competency, knowledge processes and firm performance. Industrial Management & Data Systems, 112(4), 644–662.
Petter, S., DeLone, W., and McLean, E. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29(4), pp. 7–61.
Podsakoff, P. M., MacKenzie, S. B., Lee, J., and Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879–903.
Popovič, A., Hackney, R., Coelho, P. S., and Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decision Support Systems, 54(1), pp. 729–739.
Porter, M. E. (1996). What is strategy? Harvard Business Review (74:6), pp. 61–78.
Purvis, R. L., Sambamurthy, V., and Zmud, R. W. (2001). The Assimilation of knowledge platforms in organizations: An empirical investigation. Organization Science, 12(2), 117–135.
Rahimi, F., Møller, C., and Hvam, L. (2016). Business process management and IT management: The missing integration. International Journal of Information Management, 36(1), 142–154.
Rai, A., Patnayakuni, R., and Seth, N. (2006). Firm perfiormance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, (30:2), pp. 225–246.
Ravichandran, T., and Lertwongsatien, C. (2005). Effect of information systems resources and capabilities on firm performance: A resource-based perspective. Journal of Management Information Systems, 21(4), 237–276.
Ryan, S. D., and Gates, M. S. (2004). Inclusion of social subsystem issues in IT investment decisions: An empirical assessment. Information Resources Management Journal, 17(1), 1–18.
Ryan, S. D., and Harrison, D. A. (2000). Considering social subsystem costs and benefits in information technology investment decisions: A view from the field on anticipated payoffs. Journal of Management Information Systems, 16(4), 11–40.
Ryan, S. D., Harrison, D. A., and Schkade, L. L. (2002). Information-technology investment decisions: When do costs and benefits in the social subsystem matter? Journal of Management Information Systems, 19(2), 85–127.
Sambamurthy, V., and Zmud, R. W. (1997). At the heart of success: Organization-wide management competencies in C. Sauer and P. W. Yetton (eds.), Steps to the future: Fresh thinking on the management of IT-based organizational transformation. San Francisco: Jossey-Bass, 143–163.
Santhanam, R., and Hartono, E. (2003). Issues in linking information technology capability to firm performance. MIS Quarterly, 27(1), 125–153.
Seddon, P. B., Constantinidis, D., Tamm, T., and Dod, H. (2017). How does business analytics contribute to business value? Information Systems Journal, 27(3), pp. 237–269.
Shamim, S., Zeng, J., Shariq, S. M., and Khan, Z. (2018). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information & Management, 56(6).
Shehzad, R., Khan, M., and Naeem, M. (2013). Integrating knowledge management with business intelligence processes for enhanced organizational learning. International Journal of Software Engineering and Its Applications, 7(2), 83–91.
Shollo, A. and Kautz, K. (2010). Towards an understanding of business intelligence. In the proceedings of the 21st Australian conference in Information Systems (ACIS), Brisbane.
Subramani, M. (2004). How do suppliers benefit from information technology use in supply chain relationships? MIS Quarterly, 28(1), 45–73.
Tamm, T., Seddon, P. B., and Shanks, G. (2013). Pathways to Value from Business Analytics. in Proceedings of the Thirty-Fourth International Conference on Information Systems, Milan, Italy, December, pp. 1–16.
Teece, D. J. (2000). Strategies for managing knowledge assets: the role of firm structure and industrial context. Long Range Plann, 33, 35–54.
Tippins, M. J., and Sohi, R. S. (2003). IT competency and firm performance: Is organizational learning a missing link? Strategic Management Journal, 24(8), 745–761.
Torres, R., Sidorova, A., and Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: a dynamic capabilities perspective. Information & Management, 55(7), 822–839.
Van, D. Z., J., and De, J. B. (1999). Alignment is not enough: integrating business and information technology management with the balanced business scorecard. Journal of Management Information Systems, 16, 137–156.
Visinescu, L. L., Jones, M.C., and Sidorova, A. (2017). Improving decision quality: the role of business intelligence. Journal of Computer Information Systems, 57(1), 58–66.
Wade, M. and Hulland, J. (2004). The resource-based view and information systems research: review, extension, and suggestions for future research. MIS Quarterly, 28(1), 107–142.
Wang, H. C. (2014). Distinguishing the adoption of business intelligence systems from their implementation: The role of managers’ personality profiles. Behaviour and Information Technology, 33(10), 1082–1092.
Wang, Y., Shi, S., Nevo, S., Li, S., and Chen, Y. (2015). The interaction effect of IT assets and IT management on firm performance: A systems perspective. International Journal of Information Management, 35(5), 580–593.
Watson, H. J., Haines, M., and Loiacono, E. T. (1998). The approval of data warehousing projects: Findings from ten case studies. Journal of Data Warehousing, 3(3), pp. 29–38.
Weill, P., and Aral, S., (2003). Managing the IT portfolio (update circa 2003). MIT Sloan Manag, Rev, (Res. Brief.) III (1C).
Weill, P., Subramani, M., and Broadbent, M. (2002). IT infrastructure for strategic agility. Sloan Management Review, 44(1), 57–65.
Wieder, B., and Ossimitz, M. L. (2015). The impact of business intelligence on the quality of decision making – a mediation model. Procedia Computer Science, 64, 1163–1171.
Wixom, B. H., and Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), pp. 17–41.
Wixom, B. H., Watson, H. J., and Werner, T. (2011). Developing an enterprise business intelligence capability: The norfolk southern journey. MIS Quarterly Executive, 10(2).
Wixom, B. H., Watson, H. J., Reynolds, A. M., and Hoffer, J. A. (2008). Continental airlines continues to soar with business intelligence. Information Systems Management, 25(2), pp. 102–112.
Yeoh, W., and Koronios, A. (2010). Critical success factors for business intelligence systems. Journal of Computer Information Systems, 50(3), 23–32.
指導教授 王存國(Tswen-Gwo Wang) 審核日期 2021-7-5
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明