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Toward a continuum of measurement scales in Just-in-Time (JIT) research – an examination of the predictive validity of single-item and multiple-item measures

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Abstract

We compare the predictive validity of single-item and multiple-item measures utilized in Just-in-Time (JIT) research. The study examines if single-item measures could be used for some of the JIT practices, especially if the object of inquiry is concrete singular and if the attribute to be researched is concrete. Arguments are developed for the concrete nature of the JIT practice of “set-up time reduction” and we examine the ability of a single-item measure of this variable to predict the criterion variable (delivery performance). In addition, the study also examines the efficacy of using multiple-item measures for variables that are abstract in nature, and thereby attempts to develop a continuum of JIT constructs ranging from concrete to abstract. The results obtained by analyzing two sets of survey data show that multiple-item measures are not necessarily more valid than single-item measures for all constructs. The findings provide evidence that multiple-item measures and single-item measures for scale development should be contingent upon the nature of constructs. For concrete constructs, single-item measures are as valid as multi-item measures. Meanwhile, for abstract constructs it is important to ensure that multiple items are considered to capture the multi-dimensional nature of these constructs. Results also reveal that JIT practices display significant differences in terms of abstract/concrete perceptions. The paper presents theoretical and practical implications of the findings, and offers directions for future research.

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References

  • Ahmad S, Schroeder R (2001) The impact of electronic data interchange on delivery performance. Prod Oper Manag 10(1):16–30

    Article  Google Scholar 

  • Armstrong JS, Overton TS (1977) Estimating non-response bias in mail surveys. J Mark Res 16(August): 396–402

  • Bacharach S (1989) Organizational theories: some criteria for evaluation. Acad Manag Rev 14(4):496–515

    Google Scholar 

  • Bagozzi R (1982) The role of measurement in theory construction and hypothesis testing: toward a holistic model. In: Fornell C (ed) A second generation of multivariate analysis. Praeger Publishers, New York

    Google Scholar 

  • Belekoukias I, Garza-Reyes JA, Kumar V (2014) The impact of lean methods and tools on the operational performance of manufacturing organisations. Int J Prod Res 52(18):5346–5366. doi:10.1080/00207543.2014.903348

    Article  Google Scholar 

  • Bergkvist L, Rossiter J (2007) The predictive validity of multiple-item versus single-item measures of the same constructs. J Mark Res 44(2):175–184

    Article  Google Scholar 

  • Bergkvist L, Rossiter J (2009) Tailor-made single-item measures of doubly concrete constructs. Int J Advert 28(4):607–621

    Article  Google Scholar 

  • Bortolotti T, Danese P, Romano P (2013) Assessing the impact of just-in-time on operational performance at varying degrees of repetitiveness. Int J Prod Res 51(4):1117–1130

    Article  Google Scholar 

  • Bortolotti T, Danese P, Flynn B, Romano P (2015) Leveraging fitness and lean bundles to build the cumulative performance sand cone model. Int J Prod Econ 162:227–241

    Article  Google Scholar 

  • Chase R, Erikson W (1988) The service factory. Acad Manag Exec 2(3):191–196

    Article  Google Scholar 

  • Chen IJ, Paulraj A, Lado AA (2004) Strategic purchasing, supply management, and firm performance. J Oper Manag 22(5):505–523

    Article  Google Scholar 

  • Christensen W, Germain R, Birou L (2005) Build-to-order and just-in-time as predictors of applied supply chain knowledge and market performance. J Oper Manag 23(5):470–481

    Article  Google Scholar 

  • Churchill G (1979) A paradigm for developing better measures of marketing constructs. J Mark Res: 64–73

  • Claycomb C, Dröge C, Germain R (1999) The effect of just-in-time with customers on organizational design and performance. Int J Logist Manag 10(1):37–58

    Article  Google Scholar 

  • Crawford KM, Cox JF (1990) Designing performance measurement systems for just-in-time operations. Int J Prod Res 28(11):2025–2036. doi:10.1080/00207549008942850

    Article  Google Scholar 

  • Cua K, McKone K, Schroeder R (2001) Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. J Oper Manag 19(6):675–694

    Article  Google Scholar 

  • Damanpour F (1987) The adoption of technological, administrative, and ancillary innovations: impact of organizational factors. J Manag 13(4):675–688

    Google Scholar 

  • De Toni A, Zipponi L (1991) Operating levels in product and process design. Int J Oper Prod Manag 11(6):38–54

    Article  Google Scholar 

  • Dean J Jr, Snell S (1996) The strategic use of integrated manufacturing: an empirical examination. Strateg Manag J 17(6):459–480. doi:10.1002/(SICI)1097-0266(199606)17:6<459::AID-SMJ823>3.0.CO;2-8

    Article  Google Scholar 

  • DeSalvo K, Fisher W, Tran K, Bloser N, Merrill W, Peabody J (2006) Assessing measurement properties of two single-item general health measures. Qual Life Res 15(2):191–201

    Article  Google Scholar 

  • Diamantopoulos A (2005) The C-OAR-SE procedure for scale development in marketing: a comment. Int J Res Mark 22(1):1–9

    Article  Google Scholar 

  • Diamantopoulos A, Siguaw J, Cadogan J (2008) Measuring abstract constructs in management and organizational research: the case of export coordination. Br J Manag 19(4):389–395

    Article  Google Scholar 

  • Dillman D (1978) Mail and telephone surveys. Vol. 3. Wiley Interscience

  • Dobrev S, Kim T-Y (2006) Positioning among organizations in a population: moves between market segments and the evolution of industry structure. Adm Sci Q 51(2):230–261

    Article  Google Scholar 

  • Droge C, Germain R (1998) The just-in-time inventory effect: does it hold under different contextural, environmental and organizational conditions?. J Bus Logist

  • Edwards J, Bagozzi R (2000) On the nature and direction of relationships between constructs and measures. Psychol Methods 5(2):155

    Article  Google Scholar 

  • Evan W (1966) Organizational lag. Hum Organ 25(1):51–53

    Article  Google Scholar 

  • Fawcett S, Myers M (2001) Product and employee development in advanced manufacturing: implementation and impact. Int J Prod Res 39(1):65–79

    Article  Google Scholar 

  • Fawcett SE, Scully J (1995) A contingency perspective of just-in-time purchasing: globalization, implementation, and performance. Int J Prod Res 33(4):915–931. doi:10.1080/00207549508930186

    Article  Google Scholar 

  • Finn A, Kayande U (2005) How fine is C-OAR-SE? A generalizability theory perspective on Rossiter’s procedure. Int J Res Mark 22(1):11–21

    Article  Google Scholar 

  • Flynn B, Sakakibara S, Schroeder R, Bates K, Flynn EJ (1990) Empirical research methods in operations management. J Oper Manag 9(2):250–284

    Article  Google Scholar 

  • Flynn B, Sakakibara S, Schroeder R (1995) Relationship between JIT and TQM: practices and performance. Acad Manag J 38(5):1325–1360

    Article  Google Scholar 

  • Forza C (1996) Achieving superior operating performance from integrated pipeline management: an empirical study. Int J Phys Distrib Logist Manag 26(9):36–63

    Article  Google Scholar 

  • Forza C (2002) Survey research in operations management: a process-based perspective. Int J Oper Prod Manag 22(2):152–194

    Article  Google Scholar 

  • Forza C, Vinelli A (1998) On the contribution of survey research to the development of operations management theories. In: Coughlan P, Dromgoole T, Peppard J (eds) Operations management: future issues and competitive responses. School of Business Studies, Dublin, pp 183–188

    Google Scholar 

  • Frohlich M (2002) Techniques for improving response rates in OM survey research. J Oper Manag 20(1):53–62

    Article  Google Scholar 

  • Fullerton R, McWatters C (2001) The production performance benefits from JIT implementation. J Oper Manag 19(1):81–96

    Article  Google Scholar 

  • Furlan A, Vinelli A, Dal Pont G (2011) Complementarity and lean manufacturing bundles: an empirical analysis. Int J Oper Prod Manag 31(8):835–850

    Article  Google Scholar 

  • Gardner D, Cummings L, Dunham R, Pierce J (1998) Single-item versus multiple-item measurement scales: an empirical comparison. Educ Psychol Meas 58(6):898–915

    Article  Google Scholar 

  • Germain R, Dröge C, Spears N (1996) The implications of just-in-time for logistics organization management and performance. J Bus Logist

  • Golhar D, Stamm C (1991) The just-in-time philosophy: a literature review. Int J Prod Res 29(4):657–676

    Article  Google Scholar 

  • Hair JF, Black WC, Babin BJ, Anderson RE (2010) Multivariate data analysis. 7th edn. Prentice Hall, Upper Saddle River, New Jersey

  • Hall R (1983) Zero inventories. Dow Jones-Irwin, Homewood

    Google Scholar 

  • Hempel C (1953) Methods of concept formation in science, International encyclopedia of unified science. University of Chicago Press, Chicago

    Google Scholar 

  • Hempel C (1956) A logical appraisal of operationism, The validation of science theories. Beacon, Boston

    Google Scholar 

  • Hopp W, Spearman M, Woodruff D (1990) Practical strategies for lead time reduction. Manuf Rev 3(2):78–84

    Google Scholar 

  • Im J, Lee S (1989) Implementation of just-in-time systems in US manufacturing firms. Int J Oper Prod Manag 9(1):5–14

    Article  Google Scholar 

  • Inman RA, Sale RS, Green K Jr, Whitten D (2011) Agile manufacturing: relation to JIT, operational performance and firm performance. J Oper Manag 29(4):343–355

    Article  Google Scholar 

  • Kaynak H (2002) The relationship between just-in-time purchasing techniques and firm performance. IEEE Trans Eng Manag 49(3):205--217

  • Keller S, Savitskie K, Stank T, Lynch D, Ellinger A (2002) A summary and analysis of multi‐item scales used in logistics research. J Bus Logist 23(2):83–119

    Article  Google Scholar 

  • Ketokivi M, Schroeder R (2004) Manufacturing practices, strategic fit and performance: a routine-based view. Int J Oper Prod Manag 24(2):171–191

    Article  Google Scholar 

  • Killgore W (1999) The visual analogue mood scale: can a single-item scale accurately classify depressive mood state? Psychol Rep 85(3f):1238–1243

    Article  Google Scholar 

  • Kwon H, Trail G (2005) The feasibility of single-item measures in sport loyalty research. Sport Manag Rev 8(1):69–88

    Article  Google Scholar 

  • Lambert DM, Harrington TC (1990) Measuring non-response bias in customer service mail surveys. J Bus Logist 11(2):5–25

    Google Scholar 

  • Li S, Subba Rao S, Ragu-Nathan T, Ragu-Nathan B (2005) Development and validation of a measurement instrument for studying supply chain management practices. J Oper Manag 23(6):618–641

    Article  Google Scholar 

  • Loo R (2002) A caveat on using single-item versus multiple-item scales. J Manag Psychol 17(1):68–75

    Article  Google Scholar 

  • Mackelprang A, Nair A (2010) Relationship between just-in-time manufacturing practices and performance: a meta-analytic investigation. J Oper Manag 28(4):283–302

    Article  Google Scholar 

  • Malhotra M, Grover V (1998) An assessment of survey research in POM: from constructs to theory. J Oper Manag 16(4):407–425

    Article  Google Scholar 

  • Mehra S, Inman RA (1992) Determining the critical elements of just‐in‐time implementation. Decis Sci 23(1):160–174

    Article  Google Scholar 

  • Narasimhan R, Swink M, Kim SW (2006) Disentangling leanness and agility: an empirical investigation. J Oper Manag 24(5):440–457

    Article  Google Scholar 

  • Netemeyer R, Bearden W, Sharma S (2003) Scaling procedures: issues and applications. Sage Publications

  • Nunnally J, Bernstein I (1994) Psychometric theory. In: McGraw-Hill, New York

  • Oshagbemi T (1999) Overall job satisfaction: how good are single versus multiple-item measures? J Manag Psychol 14(5):388–403

    Article  Google Scholar 

  • Poppo L, Zenger T (1998) Testing alternative theories of the firm: transaction cost, knowledge‐based, and measurement explanations for make‐or‐buy decisions in information services. Strateg Manag J 19(9):853–877

    Article  Google Scholar 

  • Rabinovich E, Dresner M, Evers P (2003) Assessing the effects of operational processes and information systems on inventory performance. J Oper Manag 21(1):63–80

    Article  Google Scholar 

  • Robins R, Hendin H, Trzesniewski K (2001) Measuring global self-esteem: construct validation of a single-item measure and the Rosenberg self-esteem scale. Personal Soc Psychol Bull 27(2):151–161

    Article  Google Scholar 

  • Rossiter J (2002) The C-OAR-SE procedure for scale development in marketing. Int J Res Mark 19(4):305–335

    Article  Google Scholar 

  • Rossiter J (2005) Reminder: a horse is a horse. Int J Res Mark 22(1):23–25

    Article  Google Scholar 

  • Rungtusanatham MJ, Choi T, Hollingworth D, Wu Z, Forza C (2003) Survey research in operations management: historical analyses. J Oper Manag 21(4):475–488

    Article  Google Scholar 

  • Sakakibara S, Flynn B, Schroeder R (1993) A framework and measurement instrument for just‐in‐time manufacturing. Prod Oper Manag 2(3):177–194

    Article  Google Scholar 

  • Sakakibara S, Flynn B, Schroeder R, Morris W (1997) The impact of just-in-time manufacturing and its infrastructure on manufacturing performance. Manag Sci 43(9):1246–1257

    Article  Google Scholar 

  • Scannell T, Vickery S, Droge C (2000) Upstream supply chain management and competitive performance in the automotive supply industry. J Bus Logist 21 (1)

  • Shah R, Goldstein S (2006) Use of structural equation modeling in operations management research: looking back and forward. J Oper Manag 24(2):148–169

    Article  Google Scholar 

  • Shah R, Ward P (2003) Lean manufacturing: context, practice bundles, and performance. J Oper Manag 21(2):129–149

    Article  Google Scholar 

  • Simons T, Pelled L, Smith K (1999) Making use of difference: diversity, debate, and decision comprehensiveness in top management teams. Acad Manag J 42(6):662–673

    Article  Google Scholar 

  • Staats B, Brunner D, Upton D (2011) Lean principles, learning, and knowledge work: evidence from a software services provider. J Oper Manag 29(5):376–390

    Article  Google Scholar 

  • Stoll H (1988) Design for manufacture. Manuf Eng 100(1):67–73

    Google Scholar 

  • Sugimori Y, Kusunoki K, Cho F, Uchikawa S (1977) Toyota production system and Kanban system materialization of just-in-time and respect-for-human system. Int J Prod Res 15(6):553–564

    Article  Google Scholar 

  • Swink M, Narasimhan R, Kim SW (2005) Manufacturing practices and strategy integration: effects on cost efficiency, flexibility, and market‐based performance. Decis Sci 36(3):427–457

    Article  Google Scholar 

  • Tedin K, Hofstetfer CR (1982) The effect of cost and importance factors on the return rate for single and multiple mailings. Public Opin Q 46(1):122–128

    Article  Google Scholar 

  • Upton D (1998) Just-in-time and performance measurement systems. Int J Oper Prod Manag 18(11):1101–1110

    Article  Google Scholar 

  • Venkatraman N (1989) Strategic orientation of business enterprises: the construct, dimensionality, and measurement. Manag Sci 35(8):942–962

    Article  Google Scholar 

  • Wacker J (2004) A theory of formal conceptual definitions: developing theory-building measurement instruments. J Oper Manag 22(6):629–650

    Article  Google Scholar 

  • Wanous J, Hudy M (2001) Single-item reliability: a replication and extension. Organ Res Methods 4(4):361–375

    Article  Google Scholar 

  • Wanous J, Reichers A, Hudy M (1997) Overall job satisfaction: how good are single-item measures? J Appl Psychol 82(2):247

    Article  Google Scholar 

  • Ward P, Zhou H (2006) Impact of information technology integration and lean/just‐in‐time practices on lead‐time performance. Decis Sci 37(2):177–203

    Article  Google Scholar 

  • White R, Pearson J, Wilson J (1999) JIT manufacturing: a survey of implementations in small and large US manufacturers. Manag Sci 45(1):1–15

    Article  Google Scholar 

  • Yammarino F, Skinner S, Childers T (1991) Understanding mail survey response behavior a meta-analysis. Public Opin Q 55(4):613–639

    Article  Google Scholar 

  • Zacharia Z, Mentzer J (2004) Logistics salience in a changing environment. J Bus Logist 25(1):187–210

    Article  Google Scholar 

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Nair, A., Ataseven, C., Habermann, M. et al. Toward a continuum of measurement scales in Just-in-Time (JIT) research – an examination of the predictive validity of single-item and multiple-item measures. Oper Manag Res 9, 35–48 (2016). https://doi.org/10.1007/s12063-016-0108-x

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