Top

Global Journal of Flexible Systems Management

Published in:

01-03-2015 | Original Article

Performance Measurement in Banking & Software Firm: An Empirical Research

Authors: Ajay Kumar Behera, Narayan C. Nayak, Harish C. Das

Published in: Global Journal of Flexible Systems Management | Issue 1/2015

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

This research develops principles for an evaluation criterion of the performance of service firm. The relationship between Information Technology (IT) adoption and the performance of firms is not well characterized. The aim of this research is to provide an analysis on the relationship between IT adoption with its usage and IT performance in Indian banking and software firms. IT performance was measured with the help of three important variables: efficiency, effectiveness, and productivity. Each one of the above has been described with a set of pretested questionnaires that were designed for the respondents from the selected firm. Empirical data was collected in the year 2013. A scientific sampling scheme was implemented using the probability sampling technique. Perceptions of branch managers, staff members and customers were collected using survey methodology. Hypothesized relationships between IT adoption and IT performance are empirically tested using survey data from service firms. The relationships between the two, as tested through correlation analyses, are found to be dependent on the IT usage and IT literacy level. IT performance was found to have a positive correlation with factors such as efficiency, effectiveness as well as profitability of service firm. Tenure of IT adoption and utility of IT contributes much towards increase in performance of firms. The analysis suggested that IT usage has a positive linear relationship with IT performance. Overall, this research highlights the complexity of the relationship between IT adoption and IT performance. This research calls for caution in defending IT as universally efficient solutions, and argues that their productivity is linked to the complementary introduction of organizational and technological innovations. This study is conducted in a specific sector, so the results cannot be generalized.

previous article Managing Wastivity for Sustainability

next article Flexible Decision Modeling for Evaluating the Risks in Green Supply Chain Using Fuzzy AHP and IRP Methodologies

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Adriaan, V. H. N., & Liliane, P. (2014). Development of a maintenance performance measurement framework using the analytic network process (ANP) for maintenance performance indicators selection. Omega, 42, 33–46.CrossRef

Arasli, H. A. (2005). Comparison of service quality in the banking industry: some evidence from Turkish- and Greek-speaking areas in Cyprus. International Journal of Bank Marketing, 23(7), 508–526.CrossRef

Bergendahl, G., & Lindblom, T. (2008). Evaluating the performance of Swedish savings banks according to service efficiency. European Journal of Operational Research, 185, 1663–1673.CrossRef

Braz, R. G. F., Scavarda, L. F., & Martins, R. A. (2011). Reviewing and improving performance measurement systems: an action research. International Journal of Production Economics, 133, 751–760.CrossRef

Calabrese, A. (2012). Service productivity and service quality: a necessary trade-off. International Journal of Production Economics, 135, 800–812.CrossRef

Chan, F. T. S., Nayak, A., Raj, R., Chong, A. Y. L., & Tiwari, M. (2014). An innovative supply chain performance measurement system incorporating research and development (R&D) and marketing policy. Computers & Industrial Engineering, 69, 64–70.CrossRef

Chan, H. C. Y., & Ngai, E. W. T. (2010). What makes customers discontent with service providers? Information and communication technology services. Journal of Business Ethics, 91, 73–110.CrossRef

Chen, J. S., & Tsou, Hung T. (2012). Performance effects of IT capability, service process innovation, and the mediating role of customer service. Journal of Engineering and Technology Management, 29, 71–94.CrossRef

Cheng, C. C., & Cheng, W. Y. (2007). Customer-focused and product-line-based manufacturing performance measurement. International Journal of Advanced Manufacturing Technology, 34, 1236–1245.CrossRef

Cheng, C. C., & Krumwiede, D. (2012). The role of service innovation in the market orientation—new service performance linkage. Technovation, 32, 487–497.CrossRef

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technologies. MIS Quarterly, 13(3), 319–340.CrossRef

Dewhurst, F. W., Lorente, A. R. M., & Rodriguez, C. S. (2003). An initial assessment of the influence of IT on TQM: a multiple case study. International Journal of Operations & Production Management, 23(4), 348–374.CrossRef

Grigoroudis, N. E., Orfanoudaki, E., & Zopounidis, C. (2012). Strategic performance measurement in a healthcare organisation: a multiple criteria approach based on balanced scorecard. Omega, 40, 104–119.CrossRef

Gupta, Y. P., & Somers, T. M. (1996). Business strategy, manufacturing flexibility, and organizational performance relationships: a path analysis approach. Production and Operations Management, 5(3), 204–233.CrossRef

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tathan, R. L. (2009). Multivariate data analysis: a global perspective (7th ed.). Upper Saddle River: PHI Publication.

Hussain, M. M., & Gunasekaran, A. (2002). Management accounting and performance measures in Japanese banks. Managing Service Quality, 12(4), 232–245.CrossRef

Jun, M., & Cai, S. (2010). The key determinants of internet bank service quality: a content analysis. International Journal of Bank Marketing, 19(7), 276–291.CrossRef

Larso, D., Doolen, T., & Hacker, M. (2009). Development of a manufacturing flexibility hierarchy through factor and cluster analysis. Journal of Manufacturing Technology Management, 20(4), 417–441.CrossRef

Lee, P. K. C., Cheng, T. C. E., Yeung, A. C. L., & Lai, K. H. (2011). An empirical study of transformational leadership, team performance and service quality in retail banks. Omega, 39, 690–701.CrossRef

Lepmets, M., Mesquida, A. L., Cater, S. A., Mas, A., & Ras, E. (2014). The evaluation of the IT service quality measurement framework in industry. Global Journal of Flexible Systems Management, 15(1), 39–57.CrossRef

Lima, E. P., Costa, S. E., Gouvea, d, Angelis, J. J., & Munik, J. (2013). Performance measurement systems: a consensual analysis of their roles. International Journal of Production Economics, 146, 524–542.CrossRef

Mutula, S. M., & Brake, P. V. (2007). ICT skills readiness for the emerging global digital economy among small businesses in developing countries. Library Hi Tech, 25(2), 231–245.CrossRef

Na, K. S., Simpson, J. T., Li, X., Singh, T., & Kim, K. Y. (2007). Software development risk and project performance measurement: Evidence in Korea. The Journal of Systems and Software, 80, 596–605.CrossRef

Needle, D. (2006). Business in context: an introduction to business and its environment, 4th ed, Thomsons, 26.

Nik, N. E. M., & Kamaruzzamanb, S. N. (2011). Assessing the maintenance aspect of facilities management through a performance measurement system: a Malaysian case study. Procedia Engineering, 20, 329–338.CrossRef

Nudurupati, S., Arshad, T., & Turner, T. (2007). Performance measurement in the construction industry: an action case investigating manufacturing methodologies. Computers in Industry, 58, 667–676.CrossRef

Nudurupati, S. S., Bititci, U. S., Kumar, V., & Chan, F. T. S. (2011). State of the art literature review on performance measurement. Computers & Industrial Engineering, 60, 29–279.CrossRef

Ojha, D., Salimath, M., & D’Souza, D. (2014). Disaster immunity and performance of service firms: the influence of market acuity and supply network partnering. International Journal Production Economics, 147, 385–397.CrossRef

Palanisamy, R. (2012). Building information systems flexibility in SAP-LAP framework: A case study evidence from SME sector. Global Journal of Flexible Systems Management, 13(1), 57–74.

Ray, P. K., & Sahu, S. (1990). Productivity measurement through multi-criteria decision making. Engineering Costs and Production Economics, 20, 151–163.CrossRef

Robinson, C., & Mahony, M. O. (2003). The Growth of ICT and industry performance. National Institute Economic Review, 184(1), 60–73.CrossRef

Rockman, I. E. (2005). Editorial ICT literacy. Reference Services Review, 33(2), 141–143.CrossRef

Schmidberger, S., Bals, L., Hartmann, E., & Jahns, C. (2009). Ground handling services at European hub airports: development of a performance measurement system for benchmarking. International Journal of Production Economics, 117, 104–116.CrossRef

Shaik, M. N., & Abdul, K. W. (2014). Comprehensive performance measurement and causal-effect decision making model for reverse logistics enterprise. Computers & Industrial Engineering, 68, 87–103.CrossRef

Steigenberger, N. (2014). Only a matter of chance? How firm performance measurement impacts study. European Management Journal, 32, 46–65.CrossRef

Therrien, P., David, D., & Tyler, C. (2011). Innovation novelty and (commercial) performance in the service sector: a Canadian firm-level analysis. Technovation, 31, 655–665.CrossRef

Trachta, K., Niesteggeb, A., & Schuha, P. (2013). Demand planning based on performance measurement systems in closed loop supply chains. Procedia CIRP, 12, 324–329.CrossRef

Wainwright, D., & Yarrow, D. (2005). Towards a framework for benchmarking ICT practice, competence and performance in small firms. The International Journal for Library and Information Services, 6(1), 39–52.

Yadav, N. (2014). Flexibility aspects in performance management system: An illustration of flexible strategy game-card. Global Journal of Flexible Systems Management, 15(3), 181–189.

Yee, R. W. Y., Lee, P. K. C., Yeung, A. C. L., & Cheng, T. C. E. (2013). The relationships among leadership, goal orientation, and service quality in high-contact service industries: an empirical study. International Journal Production Economics, 141, 452–464.CrossRef

Title: Performance Measurement in Banking & Software Firm: An Empirical Research
Authors: Ajay Kumar Behera
Narayan C. Nayak
Harish C. Das
Publication date: 01-03-2015
Publisher: Springer India
Published in: Global Journal of Flexible Systems Management / Issue 1/2015
Print ISSN: 0972-2696
Electronic ISSN: 0974-0198
DOI: https://doi.org/10.1007/s40171-014-0083-8

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 1/2015

Development of Enhanced Marketing Flexibility by Optimally Allocating Sales Campaign Days for Maximizing Total Expected Sales

Total Interpretive Structural Modeling (TISM) of the Enablers of a Flexible Control System for Industry

Managing Wastivity for Sustainability

Strategic Human Resource Management Practices and Competitive Priorities of the Manufacturing Performance in Karachi

Fuzzy-TISM: A Fuzzy Extension of TISM for Group Decision Making

Flexible Decision Modeling for Evaluating the Risks in Green Supply Chain Using Fuzzy AHP and IRP Methodologies