Skip to main content
SpringerLink
Log in

Q-TAM: a quality technology acceptance model for technology operations managers

  • Published:
Operations Management Research Aims and scope Submit manuscript

Abstract

This paper contributes to research on the quality factors that affect customer acceptance and intention to continue purchasing disposable technology. We have developed a model (Q-TAM) that integrates the Technology Acceptance Model and a quality framework. We conducted a survey of 322 smartphones users and analyzed the results using Partial Least Squares – Structural Equation Modeling (PLS-SEM) to determine how our integrated Q-TAM model affected consumers’ intention-to-continue-purchasing disposable technology. The PLS-SEM analysis of the Q-TAM model established that consumers assessed the product quality based on two distinct dimensions: attribute quality and reliability quality. Further, we found support for the positive and significant effects of product quality and perceived ease of use as predictors of a customer’s intention to purchase a technological device. Of interest is our finding that perceived usefulness, in the presence of product quality, is not significant. The finding also suggests that customers perceive the usefulness of a product as a component/part of a product’s quality dimension, confirming Joseph Juran’s quality philosophy of “fitness of use.” This suggests that in order to satisfy consumer demands, technology operations managers must ensure their products are of good attribute and reliability quality. The findings of this study make a case for a quality technology acceptance model (Q-TAM) that encourages technology operations managers to focus their efforts on quality to ensure that their products satisfy customer needs and are perceived as useful.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Adams DA, Nelson RR, Todd PA (1992) Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Quart 16(2):227–248

    Article  Google Scholar 

  • Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, New Jersey

    Google Scholar 

  • Andreev P, Heart T, Maoz H, Pliskin N (2009) Validating formative Partial Least Squares (PLS) models: Methodological review and empirical illustration, in Proceedings of the Thirtieth International Conference on Information Systems. Phoenix, Arizona

  • Armstrong JS, Overton TS (1977) Estimating non-response bias in mail survey. J Mark Res 14(3):396–402

    Article  Google Scholar 

  • Ba S, Johansson WC (2008) An exploratory study of the impact of e-service process on online customer satisfaction. Prod Oper Manag 17(1):107–119

    Article  Google Scholar 

  • Babakus E, Beinstock CC, Van Scotter JR (2006) Linking perceived quality and customer satisfaction to store traffic and revenue growth. Decis Sci 35(4):713–737

    Article  Google Scholar 

  • Barclay D (1991) Interdepartmental conflict in organizational buying: the impact of the organizational context. J Mark Res 28(2):145–159

    Article  Google Scholar 

  • Becker JM, Klein K, Wetzels W (2012) Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long Range Plan 45(5/6):359–394

    Article  Google Scholar 

  • Bhattacherjee A (2001) An empirical analysis of the antecedents of electronic commerce service continuance. Decis Support Syst 32(2):201–214

    Article  Google Scholar 

  • Boakye KG, Prybutok VR, Ryan SD (2012) The intention of continued web-enabled phone service usage: a quality perspective. Oper Manage Res 5(1):14–24

    Article  Google Scholar 

  • Brown SA, Venkatesh V, Goyal S (2012) Expectation confirmation in technology use. Inf Syst Res 23(2):474–487

    Article  Google Scholar 

  • Chin WW, Todd PA (1995) On the use, usefulness and ease of structural equation modeling in MIS research: a note of caution. MIS Quart 19(2):237–246

    Article  Google Scholar 

  • Chin WW, Marcolin B, Newsted P (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. Inf Syst Res 14(2):189–217

    Article  Google Scholar 

  • Chordas L (2001) A new generation in the cross hairs. Best’s Rev 101(10):49–54

    Google Scholar 

  • Cohen J (1988) Statistical power analysis for the behavioral Sciences, 2nd edn. Lawrence Erlbaum Associates, Hillsdale

    Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance. MIS Quart 13(3):319–340

    Article  Google Scholar 

  • Davis FD, Venkatesh V (2004) Toward preprototype user acceptance testing of new information systems: implications for software project management. IEEE Trans Eng Manag 51(1):31–46

    Article  Google Scholar 

  • Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003

    Article  Google Scholar 

  • DeLone WH, McLean ER (1992) Information systems success: the quest for the dependent. Inf Syst Res 3(3):60–95

    Article  Google Scholar 

  • Delone WH, McLean ER (2003) The Delone and McLean model of information system success: a ten year update. J Manag Inf Syst 19(4):9–30

    Google Scholar 

  • Devaraj S, Fan M, Kohli R (2002) Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics. Inf Syst Res 13(3):316–333

    Google Scholar 

  • Diamantopoulos A, Winklhofer HM (2001) Index construction with formative indicators: an alternative to scale development. J Mark Res 38(2):269–277

    Article  Google Scholar 

  • Dishaw MT, Strong DM (1999) Extending the technology acceptance model with task-technology fit constructs. Inf Manag 36(1):9–21

    Article  Google Scholar 

  • Dodds WB, Monroe KB, Grewal D (1991) The effects of price brand and store information on buyers’ product evaluations. J Mark Res 28(3):307–319

    Article  Google Scholar 

  • Fabrigar LR, MacCallum RC, Wegner DT, Strahan EJ (1999) Evaluating the use of exploratory factor analysis in psychological research. Psychol Methods 4(3):272–299

    Article  Google Scholar 

  • Fayad ME, Schmidt DC (1997) Object-oriented application frameworks. Commun ACM 40(10):32–38

    Article  Google Scholar 

  • Fornell C, Larcker D (1981) Structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  • Garvin D (1984) What does product quality really mean? Sloan Manag Rev 26(1):25–43

    Google Scholar 

  • Garvin D (1987) Competing on the eight dimensions of quality. Harv Bus Rev 65(6):101–109

    Google Scholar 

  • Gefen D, Straub DW (2000) The relative importance of perceived ease-of use-in IS acceptance: a study of e-commerce acceptance. J Assoc Inf Syst 1(8):1–30

    Google Scholar 

  • Gefen D, Karahanna E, Straub DW (2003) Inexperience and experience with online stores: the importance of TAM and trust. IEEE Trans Eng Manag 50(3):307–321

    Article  Google Scholar 

  • Golder PN, Mitra D, Moorman C (2012) What is quality? An integrative framework of process and states. J Mark 76(4):1–23

    Article  Google Scholar 

  • Hair JF, Sarstedt M, Ringle CM, Mena JA (2012) An assessment of the use of partial least squares structural equation modeling in marketing research. J Acad Mark Sci 40(3):414–433

    Article  Google Scholar 

  • Harlam BA, Krishna A, Lehmann DR, Mela C (1995) Impact of bundle type, price framing and familiarirty on purchase intention. J Bus Res 33(1):57–66

    Article  Google Scholar 

  • Harman HH (1976) Modern factor analysis, 3rd edn. University of Chicago Press, Chicago

    Google Scholar 

  • Henseler J, Fassott G (2009) Testing moderating effects in PLS path models: an illustration of available procedures. In: Vinzi EV, Chin WW, Henseler J, Wang H (eds) Handbook of PLS and marketing. Springer, Berlin

    Google Scholar 

  • Hitt LM, Wue X, Zhou X (2002) Investment in enterprise resource planning: business impact and productivity measures. J Inf Syst 19(1):71–98

    Google Scholar 

  • Hong SJ, Thong JYL, Moon JY, Tam KY (2008) Understanding the behavior of mobile data services consumers. Inf Syst Front 10(4):431–445

    Article  Google Scholar 

  • Huang EM, Truong KN (2008) Breaking the disposable technology paradigm: Opportunities for sustainable interaction design for mobile phones. Proc CHI’08. ACM. 323–332

  • Juran JM (1974) Quality control handbook, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  • Kano N, Seraku K, Takahashi F, Tsuji S (1984) Attractive quality and must-be quality. J Jpn Soc Qual Control 14(2):39–48

    Google Scholar 

  • Keil M, Tan BCY, Wei KK, Saarinen T, Tuunaien V, Wassenaar A (2000) A cross-cultural study on escalation of commitment behavior in software projects. MIS Quart 24(2):299–325

    Article  Google Scholar 

  • Landrum H, Prybutok VR (2004) A service quality and success model for the information service industry. Eur J Oper Res 153(3):628–642

    Article  Google Scholar 

  • Lippert SK, Forman H (2005) Utilization of information technology: examining cognitive and experiential factors of post-adoption behavior. IEEE Trans Eng Manag 52(3):363–381

    Article  Google Scholar 

  • Lu J, Liu C, Yu CS, Yao JE (2003) Exploring the factors associated with wireless internet via mobile technology acceptance in mainland China. Commun Int Inf Manag Assoc 3(1):101–120

    Google Scholar 

  • MacKenzie SB, Podsakoff PM, Jarvis CB (2005) The problem of measurement model misspecification in behavioural and organizational research and some recommended solutions. J Appl Psychol 90(4):710–730

    Article  Google Scholar 

  • Martesen A (2007) Tweens’ satisfaction and brand loyalty in the mobile phone market. Young Consum 8(2):106–116

    Google Scholar 

  • Nunnally JC (1978) Psychometric theory, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  • Oakes W (1972) External validity and the use of real people as subjects. Am Psychol 27(10):956–962

    Article  Google Scholar 

  • Peng DX, Lai F (2012) Using partial least squares in operations management research: a practical guideline and summary of past research. J Oper Manag 30(6):467–480

    Article  Google Scholar 

  • Petter S, DeLone W, McLean E (2008) Measuring information systems success: models, dimensions, measures, and interrelationships. Eur J Inf Syst 17(3):236–263

    Article  Google Scholar 

  • Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903

    Article  Google Scholar 

  • Power and Associates, JD (2007) Wireless customers are keeping their mobile phones longer as term contracts impact the replacement cycle. WestLake Village. http://businesscenter.jdpower.com/news/pressrelease.aspx?ID=2007079. Accessed 15 November 2012

  • Ringle SM, Sarstedt M, Straub D (2012) A critical look at the use of PLS-SEM in MIS quarterly. MIS Quart 36(1):3–14

    Google Scholar 

  • Sabherwal R, Jeyaraj A, Chowa C (2006) Information systems success: individuals and organizational determinants. Manag Sci 52(12):1849–1864

    Article  Google Scholar 

  • Schenkman BN, Jonsson FU (2000) Aesthetics and preferences of web pages. Behav Inf Technol 19(5):367–377

    Article  Google Scholar 

  • Schultz DP (1969) The human subject in psychological research. Psychol Bull 72(3):214–228

    Article  Google Scholar 

  • Scott JE, Walczak S (2009) Cognitive engagement with a multimedia ERP training tool: assessing computer self-efficacy and technology acceptance. Inf Manag 46(4):221–232

    Article  Google Scholar 

  • Seddon PB (1997) A respecification and extension of the DeLone an McLean model of IS success. Inf Syst Res 8(3):240–253

    Article  Google Scholar 

  • Shang RA, Chen YC, Shen L (2005) Extrinsic versus intrinsic motivations for consumers to shop on-line. Inf Manag 42(3):401–413

    Article  Google Scholar 

  • Shim S, Eastlick MA, Lotz SL, Warrington P (2001) An online prepurchase intentions model: the role of intention to search. J Retail 77(3):397–416

    Article  Google Scholar 

  • Straub D, Keil M, Brenner W (1997) Testing the technology acceptance model across cultures: a three country study. Inf Manag 33(1):1–11

    Article  Google Scholar 

  • Tenenhaus M, Vinzi VE, Chatelin YM, Lauro C (2005) PLS path modeling. Comput Stat Data Anal 48(1):159–205

    Article  Google Scholar 

  • Terzis V, Economides AA (2011) The acceptance and use of computer based assessment. Comput Educ 56(4):1032–1044

    Article  Google Scholar 

  • Theokary C, Ren ZJ (2011) An empirical study of the relations between hospital volume, teaching status, and service quality. Prod Oper Manag 20(3):303–318

    Google Scholar 

  • Tractinsky N, Katz AS, Ikar D (2000) What is beautiful is usable. Interact Comput 13(2):127–145

    Article  Google Scholar 

  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204

    Article  Google Scholar 

  • Venkatesh V, Morris MG (2000) Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quart 24(1):115–139

    Article  Google Scholar 

  • Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Quart 27(3):425–478

    Google Scholar 

  • Venkatesh V, Bala H, Sykes TA (2010) Impacts of information and communication technology implementations on employees’ jobs in service organizations in India: a multi-method longitudinal field study. Prod Oper Manag 19(5):591–613

    Article  Google Scholar 

  • Vroom VH (1964) Work and motivation. Wiley, New York

    Google Scholar 

  • Wetzels M, Odekerken-Schröder G, van Oppen C (2009) Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quart 33(1):177–195

    Google Scholar 

  • Wixom B, Todd P (2005) A theoretical integration of user satisfaction and technology acceptance. Inf Syst Res 16(1):85–102

    Article  Google Scholar 

  • Wold H (1982) Soft modeling: the basic design and some extensions. In: Jöreskog KG, Wold H (eds) Systems under indirect observation: causality, structure, prediction, vol 2. North Holland, Amsterdam, pp 1–54

    Google Scholar 

  • Zhang X, Prybutok VR, Koh CE (2006) The role of impulsivness in a TAM-based online purchasing behavior model. Inf Resour Manag J 19(2):54–68

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management, College of Business Administration, Georgia Southern University, Statesboro, GA, USA

    Kwabena G. Boakye

  2. Department of Management, Seidman College of Business, Grand Valley State University, Grand Rapids, MI, USA

    Thomas McGinnis

  3. Department of Information Technology and Decision Sciences, College of Business, University of North Texas, Denton, TX, USA

    Victor R. Prybutok

Authors
  1. Kwabena G. Boakye
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thomas McGinnis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor R. Prybutok
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kwabena G. Boakye.

Appendix 1

Appendix 1

Table 4 ᅟ
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Boakye, K.G., McGinnis, T. & Prybutok, V.R. Q-TAM: a quality technology acceptance model for technology operations managers. Oper Manag Res 7, 13–23 (2014). https://doi.org/10.1007/s12063-014-0085-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12063-014-0085-x

Keywords

Search

Navigation