组织成员认知对组织信息系统应用绩效影响研究
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摘要
随着企业信息系统投资的增长,研究人员越来越关心信息系统的应用绩效。虽然理论界的研究结果表明信息化投资能够对组织产生价值,然而,组织在具体实践中应用信息系统的绩效并不理想。本文通过翻阅前人的研究成果,结合实践走访,认为组织成员认知因素是影响信息系统应用绩效的一个重要原因。目前,相对国外研究而言,国内学者做的实证研究并不多1。本文依据组织行为学和信息管理学的相关知识,选取了组织成员应用信息系统的认知层变量和行为层变量,构建了组织成员认知因素影响信息系统应用绩效的理论模型,同时,引入了信息系统产生的中间利益,包括工作效率、数据质量和协调性,应用实证研究方法,试图深入揭示组织成员认知因素对信息系统应用绩效的影响,为组织实践以及理论研究提供一定的参考价值。
在数据收集过程中,本文基于前人相关研究中形成的有效量表,发展了自身的研究工具,结合方便抽样和配额抽样的抽样方法,以中国制造业企业的制造部门中接触信息系统的人员为样本,于2005年5月进行了调查采集。首先在中国制造企业中抽取22家企业,然后在相关部门中抽取一定数量的接触和使用信息系统的员工。本次调查一共发出了690份调查问卷,其中回收了636份,有效问卷581份,有效率达到了91.35%。在数据分析过程中,本文采用结构方程模型(SEM)统计分析方法,利用AMOS4.0统计分析软件,对理论模型的内敛信度、判别效度和综合信度分别进行了验证,结果证明了模型信度和效度的可靠性。同时,本文还对理论模型适配指标进行了估计,总体上来看,理论模型与本研究收集的数据呈现了较合理的适配程度。并且,本文对提出的相应路径假设作了检验,指出了各变量之间的因果关系和影响程度。
研究表明,数据质量并不是影响组织应用信息系统整体绩效的直接因素,它是通过影响工作效率和协调性间接的影响组织应用信息系统的绩效。组织成员对应用信息系统结果的认知和信息系统自我效能的认知,对工作效率提高和协调性提升起着关键的作用,同时他们还影响着数据质量的提高。而组织成员对组织压力的认知只对数据质量的提高具有影响。
With the increase of investment in information systems in proportion to the total investment in the organization, the impact on performance has become the important issue. It has been evidenced that the investment in information systems is good for organization, However, the effect of the information technology/information system (IT/IS) is not satisfying in practice. With literature interviewing and organization practicing, this study discovers that the main reason which information system is unsatisfactory in practice lies in the cognition of information system by organization members. At present, quite a few scholars do the study on this field. Generally speaking, the empirical analysis that the domestic scholars do is not much enough. The study is based on the knowledge of Organizational Behavior and Information Administration, chooses the variables of Cognition and Behavior, and designs a theoretical model of the impact of cognitive variables of organization members on information system benefits. At the same time, the study has pointed out Intermediate benefits that information system produces, which include task efficiency, quality of data and coordination. Carrying on the empirical analysis, the study tries to reveal the impact of cognitive variables of organization members on information system benefits in depth and provide some guidance theoretically and practically.In the process of data collection, the study develops questionnaires according to effective scale of foregoing studies. With convenience and quota sampling methods, the sampling population was the employees who have contact with information system in the manufacturing departments in the manufacturing enterprises. We chose 22 manufacturing enterprises on May in 2005, and then selected the departments that we need. The data was collected from the employees who contact and make use of information system. We sent 690 questionnaires, and 636 were returned. The valid questionnaires were 581 and the effective rate reached 91.35%.
In the process of data analysis, the study employed the Structure Equation Modeling (SEM) and AMOS4.0 software to estimate all fit indices of proposed model, as well as consistency reliability, convergent validity and discriminate validity. The result verified that this proposed model owned acceptable goodness-of-fit with collected data. Finally, all proposed hypothesis were examined and tested by the results of Structure Equation Modeling Analysis, and then pointed out the causal relationship and the impact between the variables.
Several innovative points were produced in this study. On the one hand, the quality of data is really not the direct factor of organization overall information system benefits, but the indirect one. At first, it affects the efficiency and coordination, and then affects organization overall information system benefits indirectly. On the another hand, the impact cognition of using information system and the Self-efficacy cognition of using information system play an important role in efficiency and coordination; they also affect the data quality. However, subjective norm cognition of using information system has some impact on data quality only.
在数据收集过程中,本文基于前人相关研究中形成的有效量表,发展了自身的研究工具,结合方便抽样和配额抽样的抽样方法,以中国制造业企业的制造部门中接触信息系统的人员为样本,于2005年5月进行了调查采集。首先在中国制造企业中抽取22家企业,然后在相关部门中抽取一定数量的接触和使用信息系统的员工。本次调查一共发出了690份调查问卷,其中回收了636份,有效问卷581份,有效率达到了91.35%。在数据分析过程中,本文采用结构方程模型(SEM)统计分析方法,利用AMOS4.0统计分析软件,对理论模型的内敛信度、判别效度和综合信度分别进行了验证,结果证明了模型信度和效度的可靠性。同时,本文还对理论模型适配指标进行了估计,总体上来看,理论模型与本研究收集的数据呈现了较合理的适配程度。并且,本文对提出的相应路径假设作了检验,指出了各变量之间的因果关系和影响程度。
研究表明,数据质量并不是影响组织应用信息系统整体绩效的直接因素,它是通过影响工作效率和协调性间接的影响组织应用信息系统的绩效。组织成员对应用信息系统结果的认知和信息系统自我效能的认知,对工作效率提高和协调性提升起着关键的作用,同时他们还影响着数据质量的提高。而组织成员对组织压力的认知只对数据质量的提高具有影响。
With the increase of investment in information systems in proportion to the total investment in the organization, the impact on performance has become the important issue. It has been evidenced that the investment in information systems is good for organization, However, the effect of the information technology/information system (IT/IS) is not satisfying in practice. With literature interviewing and organization practicing, this study discovers that the main reason which information system is unsatisfactory in practice lies in the cognition of information system by organization members. At present, quite a few scholars do the study on this field. Generally speaking, the empirical analysis that the domestic scholars do is not much enough. The study is based on the knowledge of Organizational Behavior and Information Administration, chooses the variables of Cognition and Behavior, and designs a theoretical model of the impact of cognitive variables of organization members on information system benefits. At the same time, the study has pointed out Intermediate benefits that information system produces, which include task efficiency, quality of data and coordination. Carrying on the empirical analysis, the study tries to reveal the impact of cognitive variables of organization members on information system benefits in depth and provide some guidance theoretically and practically.In the process of data collection, the study develops questionnaires according to effective scale of foregoing studies. With convenience and quota sampling methods, the sampling population was the employees who have contact with information system in the manufacturing departments in the manufacturing enterprises. We chose 22 manufacturing enterprises on May in 2005, and then selected the departments that we need. The data was collected from the employees who contact and make use of information system. We sent 690 questionnaires, and 636 were returned. The valid questionnaires were 581 and the effective rate reached 91.35%.
In the process of data analysis, the study employed the Structure Equation Modeling (SEM) and AMOS4.0 software to estimate all fit indices of proposed model, as well as consistency reliability, convergent validity and discriminate validity. The result verified that this proposed model owned acceptable goodness-of-fit with collected data. Finally, all proposed hypothesis were examined and tested by the results of Structure Equation Modeling Analysis, and then pointed out the causal relationship and the impact between the variables.
Several innovative points were produced in this study. On the one hand, the quality of data is really not the direct factor of organization overall information system benefits, but the indirect one. At first, it affects the efficiency and coordination, and then affects organization overall information system benefits indirectly. On the another hand, the impact cognition of using information system and the Self-efficacy cognition of using information system play an important role in efficiency and coordination; they also affect the data quality. However, subjective norm cognition of using information system has some impact on data quality only.
引文
1 Brynjolfsson E. The Productivity Paradox of Information Technology. Communications of the ACM. 1993, 36(12):66-77
2 Brynjolfsson E., Hitt L.. Paradox Lost Firm-Level Evidence on the Returns to Information Systems Spending. Management Science. 1996, 42(4):541-558.
3 Bruce Dehning, Vernon J. Richardson. Returns on Investments in Information Technology: A Research Synthesis. Journal of Information Systems. 2002,1(6): 233~240
4 Saud Al-Sehali. The Factors that Affect the Implementation of Enterprise Resource Planning DB. 2000: 313~324
5 Hannu Kjvijarvi, Timo Saarinen. Investment in Information Systems and the Financial Performance of the Firm. Information and Management. 1995, 2(5): 3~34
6 Tam, K. Y. The Impact of Information Technology Investments on Firm Performance and Evaluation: Evidence from Newly Industrialized Economies. Information Systems Research(9:1). 1998: 85~98
7 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information technology. MIS Quarterly. 1989,13(3): 319~ 339
8 Ajzen, I. Attitudes, Personality and Behavior. Chicago, Illinois: The Dorsey Press. 1998:149~206
9 Taylor S, Todd P A. Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research. 1995,6(4): 144~ 176
10 Moore G C, Benbasat I. Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research. 1991,2(3): 192~222
11 Thompson R L, Higgins C A and Howell J M. Personal Computing: Towards A Conceptual Model of Utilization. MIS Quarterly. 1991,15(1): 124~143
12 Barua A., Mukhopadhyay T. Business Value of Information Technologies: Pase, Present and Future, in Framing The Domains of IT Management:Projecting The Future Through The Past, R. W Zmud(Ed.). Pinnaflex Educational Resources, Cincinnati, Oh. 2000: 65-84
13 Sambamurthy V., Bharadwaj A., Grover V. Shaping Agility through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms. Mis Quarterly.2003, 27(2): 237-263
14 Tanriverdi H. Information Technology Relatedness, Knowledge Management Capability, and Performance of Multi-Business Firms. MIS Quarterly. 2005, 29 (2): 311-334
15 Thomas F. Gattiker, Dale L. Goodhue. What Happens After ERP Implementation: Understanding the Impact of Interdependence And Differentiation on Plant-level Outcomes. MIS Quarterly. 2005, 29(3): 559~585
16阂庆飞,仲秋雁,陆牡丹. ERP实施中的抵制行为研究.科技管理研究. 2004,(5): 57-60
17常香云,霍佳震. ERP员工行为研究.科技进步与对策. 2005,(1): 97-98
18丘亮新.论总经理在ERP建设过程中的角色定位.福建工程学院学报. 2005,(5): 409-412
19杨海霞,王斌.企业信息系统建设中的问题与对策研究.生产力研究. 2005,(5): 184-186
20 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information technology. MIS Quarterly. 1989,13(3): 319- 339
21 Ajzen, I.. Attitudes, Personality and Behavior. Chicago, Illinois: The Dorsey Press. 1998:149-206
22 Fishbein M, Ajzen I.. Believe Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA. 1975: 52-98
23 Madden M. J., EllenP. S., Ajzen I.. A Comparison of the Theory of Planned Behavioral and the Theory of Reasoned Action. Personality and Social Psychology Bulletin. 1992,18(1):3-9
24 Godin G., Kok G.. The Theory of Planned Behavior: A Review of Its Applications to Health-related Behaviors. American Journal of Health Promotion. 1996,11(2): 87-98
25 Moore G C, Benbasat I.. Development of an Instrument to Measure thePerceptions of Adopting an Information Technology Innovation. Information Systems Research. 1991,2(3): 192-222
26 Thompson R. L., Higgins C. A., Howell J. M.. Personal Computing: Towards A Conceptual Model of Utilization. MIS Quarterly.1991,15(1): 124-143
27 A. Bandura. Social Foundations of Thought and Action: A Social Cognitive Theory. NJ: Prentice Hall. 1986: 110
28 W. L. Gardner, E. J. Rozell. Computer Efficacy: Determinants, Conseq- uences, and Malleability. The Journal of High Technology Management Research. 2000, 11(1): 109-136
29 Compeau D, Higgins C.. Computer Self-efficacy: Development of a Measure and Initial Test. MIS Quarterly. 1995,19(2): 189-211
30 Compeau D., Higgins C., Hu S.. Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study. MIS Quarterly. 1999, 23(2): 145-158
31 Vincent Kenny. An Introduction to the Personal Construct Psychology of George A. Kelly. 1998,(9):56-75
32 F. Heider. The Psychology of Interpersonal Relations. J. Wiley and Sons. New York.1958:96~113
33 Bandura A.. Self-efficacy: The exercise of control. New York: Freeman, 1997:187-203
34威廉J.史蒂文森.生产与运作管理.第6版.上海工业出版社, 2000: 28-30
35刘曙光,陈荣秋,鞠静.企业协调柔性研究.华中理工大学学报.1998, 26(2) :87-92
36 Vosburg J., Kumar A.. Managing Dirty Data in Organizations Using ERP: Lessons from a Case Study. Industrial management and Data Systems. 2001,101(1): 21-31
37 I. Ajzen, M. Fishbein. Understanding attitudes and predicting social behavior. Englewood Cliffs. N. J. Prentice-Hall. 1980: 31-102
38 Roberts S. Kaplan, David P. Norton. The Balanced Score card: Measures That Drive Performance. Harvard Business Review.1992,(1/2): 71-79
39王学民.关于样本均值的抽样分布能否作正态近似的探讨.统计研究.2005(7) :75-78
40 J. F. Hair, R. E. Anderson, R. L. Tatham, W. C. Black. Multivariate Data Analysis with Readings. 4rd edition. Macmillan. New York. 1995: 237-287
41方平,熊端琴,蔡红.结构方程在心理学研究中的应用.心理科学.2001, 24(4) : 406-408
42 B. G. Tabachnick, L. S. Fidell. Using Multivariate Ststistics. 3rd edition HarperCollins. New York. 1996: 709-796
43 Hair J. F., Anderson R. E., Ththam R. L., & Black, W. C.. Multivariate data analysis. 5th edn. Prentice Hall International. UK,1998:351-370
44 L. A. Hayduk. Structural equation modeling with LISREL: Essentials and advances. Baltimore, MD: The John Hopkins University Press, 1987: 699-760
45 Steenkamp M., Trijp M.. The Use of Lisrel in Validating Marketing Constructs, International Journal of Research in Marketing. 1991,8: 283-299
46金玉芳,董大海.消费者信任影响因素实证研究——基于过程的观点.管理世界.2004, (7):93-100
47 J. C. Nunnally. Psychometric Theory. 2nd edition. Mcraw~Hill, NewYork. 1978: 234-254
48 Bagozzi R. P., Yi, Y. On the evaluation of structural equation models. Journal of the Academy of Marketing Science.1998,16:74-94
49 Raine Eudy, Ruth. Using structural equation modeling to test for differential reliability and validity: An empirical demonstration. Structural Equation Modeling.2000, 7(1): 124-141
50 C. R. Fornell, D. F. Larcker. Structural equation models with unobservable variables and measurement error. J. Mktg Res. 1981, (18): 39-50
51 Wixon B. H., Watson H. J.. An empirical investigation of the factors affecting data werehousing success. MIS Quarterly, 2001, (25): 17-41
52阂庆飞.中国企业ERP系统实施关键成功因素的实证研究.大连理工大学博士学位论文.2004
53寸晓刚,陈顺清.影响信息系统成功的个人行为模式研究探讨.人力资源管理. 2006,(2):132-136
54郑志成,徐晓飞.制造业信息化应用工程典型示范成功案例.黑龙江科学技术出版社, 2004,(3):58-64
2 Brynjolfsson E., Hitt L.. Paradox Lost Firm-Level Evidence on the Returns to Information Systems Spending. Management Science. 1996, 42(4):541-558.
3 Bruce Dehning, Vernon J. Richardson. Returns on Investments in Information Technology: A Research Synthesis. Journal of Information Systems. 2002,1(6): 233~240
4 Saud Al-Sehali. The Factors that Affect the Implementation of Enterprise Resource Planning DB. 2000: 313~324
5 Hannu Kjvijarvi, Timo Saarinen. Investment in Information Systems and the Financial Performance of the Firm. Information and Management. 1995, 2(5): 3~34
6 Tam, K. Y. The Impact of Information Technology Investments on Firm Performance and Evaluation: Evidence from Newly Industrialized Economies. Information Systems Research(9:1). 1998: 85~98
7 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information technology. MIS Quarterly. 1989,13(3): 319~ 339
8 Ajzen, I. Attitudes, Personality and Behavior. Chicago, Illinois: The Dorsey Press. 1998:149~206
9 Taylor S, Todd P A. Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research. 1995,6(4): 144~ 176
10 Moore G C, Benbasat I. Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research. 1991,2(3): 192~222
11 Thompson R L, Higgins C A and Howell J M. Personal Computing: Towards A Conceptual Model of Utilization. MIS Quarterly. 1991,15(1): 124~143
12 Barua A., Mukhopadhyay T. Business Value of Information Technologies: Pase, Present and Future, in Framing The Domains of IT Management:Projecting The Future Through The Past, R. W Zmud(Ed.). Pinnaflex Educational Resources, Cincinnati, Oh. 2000: 65-84
13 Sambamurthy V., Bharadwaj A., Grover V. Shaping Agility through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms. Mis Quarterly.2003, 27(2): 237-263
14 Tanriverdi H. Information Technology Relatedness, Knowledge Management Capability, and Performance of Multi-Business Firms. MIS Quarterly. 2005, 29 (2): 311-334
15 Thomas F. Gattiker, Dale L. Goodhue. What Happens After ERP Implementation: Understanding the Impact of Interdependence And Differentiation on Plant-level Outcomes. MIS Quarterly. 2005, 29(3): 559~585
16阂庆飞,仲秋雁,陆牡丹. ERP实施中的抵制行为研究.科技管理研究. 2004,(5): 57-60
17常香云,霍佳震. ERP员工行为研究.科技进步与对策. 2005,(1): 97-98
18丘亮新.论总经理在ERP建设过程中的角色定位.福建工程学院学报. 2005,(5): 409-412
19杨海霞,王斌.企业信息系统建设中的问题与对策研究.生产力研究. 2005,(5): 184-186
20 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information technology. MIS Quarterly. 1989,13(3): 319- 339
21 Ajzen, I.. Attitudes, Personality and Behavior. Chicago, Illinois: The Dorsey Press. 1998:149-206
22 Fishbein M, Ajzen I.. Believe Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA. 1975: 52-98
23 Madden M. J., EllenP. S., Ajzen I.. A Comparison of the Theory of Planned Behavioral and the Theory of Reasoned Action. Personality and Social Psychology Bulletin. 1992,18(1):3-9
24 Godin G., Kok G.. The Theory of Planned Behavior: A Review of Its Applications to Health-related Behaviors. American Journal of Health Promotion. 1996,11(2): 87-98
25 Moore G C, Benbasat I.. Development of an Instrument to Measure thePerceptions of Adopting an Information Technology Innovation. Information Systems Research. 1991,2(3): 192-222
26 Thompson R. L., Higgins C. A., Howell J. M.. Personal Computing: Towards A Conceptual Model of Utilization. MIS Quarterly.1991,15(1): 124-143
27 A. Bandura. Social Foundations of Thought and Action: A Social Cognitive Theory. NJ: Prentice Hall. 1986: 110
28 W. L. Gardner, E. J. Rozell. Computer Efficacy: Determinants, Conseq- uences, and Malleability. The Journal of High Technology Management Research. 2000, 11(1): 109-136
29 Compeau D, Higgins C.. Computer Self-efficacy: Development of a Measure and Initial Test. MIS Quarterly. 1995,19(2): 189-211
30 Compeau D., Higgins C., Hu S.. Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study. MIS Quarterly. 1999, 23(2): 145-158
31 Vincent Kenny. An Introduction to the Personal Construct Psychology of George A. Kelly. 1998,(9):56-75
32 F. Heider. The Psychology of Interpersonal Relations. J. Wiley and Sons. New York.1958:96~113
33 Bandura A.. Self-efficacy: The exercise of control. New York: Freeman, 1997:187-203
34威廉J.史蒂文森.生产与运作管理.第6版.上海工业出版社, 2000: 28-30
35刘曙光,陈荣秋,鞠静.企业协调柔性研究.华中理工大学学报.1998, 26(2) :87-92
36 Vosburg J., Kumar A.. Managing Dirty Data in Organizations Using ERP: Lessons from a Case Study. Industrial management and Data Systems. 2001,101(1): 21-31
37 I. Ajzen, M. Fishbein. Understanding attitudes and predicting social behavior. Englewood Cliffs. N. J. Prentice-Hall. 1980: 31-102
38 Roberts S. Kaplan, David P. Norton. The Balanced Score card: Measures That Drive Performance. Harvard Business Review.1992,(1/2): 71-79
39王学民.关于样本均值的抽样分布能否作正态近似的探讨.统计研究.2005(7) :75-78
40 J. F. Hair, R. E. Anderson, R. L. Tatham, W. C. Black. Multivariate Data Analysis with Readings. 4rd edition. Macmillan. New York. 1995: 237-287
41方平,熊端琴,蔡红.结构方程在心理学研究中的应用.心理科学.2001, 24(4) : 406-408
42 B. G. Tabachnick, L. S. Fidell. Using Multivariate Ststistics. 3rd edition HarperCollins. New York. 1996: 709-796
43 Hair J. F., Anderson R. E., Ththam R. L., & Black, W. C.. Multivariate data analysis. 5th edn. Prentice Hall International. UK,1998:351-370
44 L. A. Hayduk. Structural equation modeling with LISREL: Essentials and advances. Baltimore, MD: The John Hopkins University Press, 1987: 699-760
45 Steenkamp M., Trijp M.. The Use of Lisrel in Validating Marketing Constructs, International Journal of Research in Marketing. 1991,8: 283-299
46金玉芳,董大海.消费者信任影响因素实证研究——基于过程的观点.管理世界.2004, (7):93-100
47 J. C. Nunnally. Psychometric Theory. 2nd edition. Mcraw~Hill, NewYork. 1978: 234-254
48 Bagozzi R. P., Yi, Y. On the evaluation of structural equation models. Journal of the Academy of Marketing Science.1998,16:74-94
49 Raine Eudy, Ruth. Using structural equation modeling to test for differential reliability and validity: An empirical demonstration. Structural Equation Modeling.2000, 7(1): 124-141
50 C. R. Fornell, D. F. Larcker. Structural equation models with unobservable variables and measurement error. J. Mktg Res. 1981, (18): 39-50
51 Wixon B. H., Watson H. J.. An empirical investigation of the factors affecting data werehousing success. MIS Quarterly, 2001, (25): 17-41
52阂庆飞.中国企业ERP系统实施关键成功因素的实证研究.大连理工大学博士学位论文.2004
53寸晓刚,陈顺清.影响信息系统成功的个人行为模式研究探讨.人力资源管理. 2006,(2):132-136
54郑志成,徐晓飞.制造业信息化应用工程典型示范成功案例.黑龙江科学技术出版社, 2004,(3):58-64