Search results

The purpose of this paper is to review and extend recent simulation studies on discriminant validity measures, contrasting the use of cutoff values (i.e. heuristics) with inferential tests.

Based on a simulation study, which considers different construct correlations, sample sizes, numbers of indicators and loading patterns, the authors assess each criterion’s sensitivity to type I and type II errors.

The findings of the simulation study provide further evidence for the robustness of the heterotrait–monotrait (HTMT) ratio of correlations criterion as an estimator of disattenuated (perfectly reliable) correlations between constructs, whose performance parallels that of the standard constrained PHI approach. Furthermore, the authors identify situations in which both methods fail and suggest an alternative criterion.

Addressing the limitations of prior simulation studies, the authors use both directional comparisons (i.e. heuristics) and inferential tests to facilitate the comparison of the HTMT and PHI methods. Furthermore, the simulation considers criteria that have not been assessed in prior research.

Supply chain management (SCM) proficiency is generally associated with superior business performance. Yet, SCM research continues to focus predominantly on the performance of individual firms, rather than on the collective performance of multiple supply chain participants as espoused by the extended enterprise (EE) concept. In response to calls for quantitative studies that examine the collective performance of multiple supply chain participants, this research study compares the combined performance of triads comprising focal firms recognized for their relative SCM proficiency and their upstream (supplier) and downstream (customer) supply chain partners with that of their close industry competitors' triads.

The triadic, longitudinal examination of multiple supply chain participants' collective performance utilized archival financial data of the period 2007–2017 from the Compustat database and the supply chain (SPLC) function of Bloomberg.

Findings of this study indicated that supply chain triads that included focal firms recognized for their relative SCM proficiency experienced significantly lower sales and general administrative expenses and significantly higher productivity, return on assets and profitability over time than their close industry competitors' triads. However, contrary to expectations, the performance advantages identified did not extend to revenue growth.

Supply chain triads cannot fully represent entire supply chains or EEs. However, this study’s triadic analysis can be viewed as a practically achievable proxy for further validating the EE concept. Moreover, based on assertions that triadic studies are suitable for SCM research and on empirical studies that consistently show individual firms recognized for their relative SCM proficiency outperform competitors, the authors contend that the study’s findings appropriately corroborate the value of the EE concept.

Because such empirical evidence is so rare, the consistent, collective performance advantages identified in this study should be highly significant to managers.

Robust, longitudinal evidence that supply chain triads which include focal firms recognized for relative SCM proficiency collectively outperform their close industry competitors' triads extends generally accepted associations between SCM proficiency and business performance, suggesting that the application of extended resource-based view (ERBV) in supply chain contexts warrants further examination and further substantiates the efficacy of the EE concept.

In response to calls for the identification of approaches that promote frontline employee (FLE) engagement, the purpose of this paper is to extend the current understanding of the influence of work design by testing competing mediating models that assess job resource and social exchange aspects of work design as either intermediate or antecedent mechanisms in reciprocal social exchanges between service provider firms and FLEs. Moderating effects of interactions between job resources and organizational support and customer focus on engagement are also assessed.

A questionnaire is administered to 525 FLEs from multiple service industries. Structural equation modeling is used to test hypotheses and examine their robustness relative to competing models. Common method bias is assessed using a confirmatory factor analysis marker variable technique.

Organizational support and customer focus are identified as proximal mediating social exchange aspects of work design that, consistent with role-specific conceptualizations of engagement, differentially influence FLE job and organization engagement.

The study findings offer insight about how firms can implement job resource and social exchange aspects of work design to favorably influence FLE engagement.

Services marketing research continues to focus more on service recipients than on FLE service providers. The examination of reciprocal social exchanges between service provider firms and FLEs sheds light on the complexities associated with exploiting aspects of work design to more effectively engage FLEs.

Purpose – Cultural distance (CD) reflects differences in cultural values across countries. Many studies have used CD to explain strategies and outcomes in international business practices, although often with limited success. This chapter demonstrates previously unrecognized problems with the conceptualization, analysis, and interpretation of CD measures and suggests methods for improvements in CD research.

Design/methodology/approach – Problems with traditional methods in CD research are demonstrated analytically and illustrated with correlation and regression analyses of secondary data. One analysis shows that individual cultural dimensions may provide alternative explanations for hypothesized effects of distance. Two other examples illustrate the incorrect conclusions that traditional analysis approaches may suggest.

Findings – The difference scores that are implicit in measures of CD usually imply unrealistic constraints on relationships between variables. Analyzing CD at the level of organizations rather than countries exaggerates the available sample size and may result in inaccurate statistical tests.

Research limitations/implications – The empirical examples illustrate problems with methodology for CD research. They are not proposed as substantive, generalizable tests of hypotheses.

Originality/value of the chapter – This chapter provides original arguments to augment existing criticisms of CD research. It shows that findings from extant CD studies may not support the conclusions that have been reported in the literature. Future research should use methods that lead to correct interpretations of CD effects.

This paper aims to respond to John Rossiter's call for a “Marketing measurement revolution” in the current issue of EJM, as well as providing broader comment on Rossiter's C‐OAR‐SE framework, and measurement practice in marketing in general.

The paper is purely theoretical, based on interpretation of measurement theory.

The authors find that much of Rossiter's diagnosis of the problems facing measurement practice in marketing and social science is highly relevant. However, the authors find themselves opposed to the revolution advocated by Rossiter.

The paper presents a comment based on interpretation of measurement theory and observation of practices in marketing and social science. As such, the interpretation is itself open to disagreement.

There are implications for those outside academia who wish to use measures derived from academic work as well as to derive their own measures of key marketing and other social variables.

This paper is one of the few to explicitly respond to the C‐OAR‐SE framework proposed by Rossiter, and presents a number of points critical to good measurement theory and practice, which appear to remain underdeveloped in marketing and social science.

The purpose of this paper is to explore the relationship between being a “great place to work” (GPTW) and firm performance. While lists such as the “Fortune 100 best places to work” were initially regarded solely as publicity vehicles for ranked firms, researchers have since tried to untangle the relationship between being a GPTW and firm performance, often by focussing on HRM systems and practices. In contrast, the study focusses on the valuable, rare, costly to imitate, and organization-exploitability aspects of being a trustworthy employer, place where workers take pride in their work and enjoy the people with whom they work.

This study uses four distinct samples of firms drawn from Fortune’s best companies to work for, Glassdoor.com’s Employees’ Choice Awards, Careerbliss.com’s 50 Happiest Companies in America, and Achievers.com’s 50 Most Engaged Workplaces Awards databases in a longitudinal design to compare performance attributes of listed firms to their respective industry peer groups.

Being a GPTW is associated with greater productivity, growth potential, and higher operating profits.

Some GPTW firms are privately held and were excluded from analysis.

Rather than focussing on individual HRM practices and techniques, employers may realize greater performance improvements by focussing on building a reputation as a trustworthy employer and fostering an environment where employees take pride in their work and enjoy working with each other.

Other GPTW studies have focussed on HRM practices as antecedents to performance outcomes, which may not accurately reflect the attributes of the GPTW construct. This study focusses squarely on the underlying attributes of being a GPTW: employer trustworthiness, worker pride, and camaraderie and how they affect firm performance.

This paper explores the reasons for the increase in “outdoor advertising” (OA) expenditures worldwide and the impact of billboards on our cities. Since 2006, a portable device that measures billboard exposure became widely available, thus setting up a rating system like that of other forms of media. Additionally, high‐resolution digital printing and state‐of‐the‐art electronic display units enabled a resurgence in the popularity of billboards. Corinthian‐pillared buildings, gothic archways, monuments, and colossal skyscrapers once defined the architectural landscape of our cities. Today outdoor advertising overpowers those landmark giants in the cities in which we live and work, as advertisers find it progressively more difficult to reach people through other media. Gargantuan billboards and other manifestations of this industry make this metamorphosis possible in urban and rural areas, from Harlem to Hong Kong.

“Garbage in, garbage out” is a common expression that academics and practitioners use to emphasize that empirical analysis is only as good as the basis on which it relies. Although the importance of sound data and valid measures has long been acknowledged, it is nevertheless often problematic to follow required quality standards in concrete research situations. Potential sources of error are usually unknown, methods to ensure data quality are unavailable, and existing methods for scale development, index construction, data collection, and data analysis are insufficient or erroneously applied. This is especially true of international marketing research, which often makes great demands on the data and measures used, as well as on the research methodology applied. Against this background, this volume addresses issues pertaining to measurement and research methodology in an international marketing context. Thanks to the efforts of authors and reviewers, we are pleased to present nine articles that deal with cutting-edge topics such as formative measurement, response-bias in cross-cultural research, marketing efficiency measurement, and segmentation methods.

Existing research on the relationship between big data and organizational decision quality is still few and far between, and what does exist often assumes direct effects of big data on decision quality. More recent research indicates that such direct effects may be too simplistic, and in particular, an organization’s overall human skills are often not considered sufficiently. Inspired by the knowledge-based view, we therefore propose that interactions between three aspects of big data usage and management accountants’ data analytics skills may be key to reaching high-quality decisions. The purpose of this study is to test these predictions based on a survey of US firms.

The authors draw on survey data from 140 US firms. This survey has been conducted via MTurk in 2020.

The results of the study show that the quality of big data sources is associated with higher perceived levels of decision quality. However, according to the results, the breadth of big data sources and a data-driven culture only improve decision quality if management accountants’ data analytics skills are highly developed. These results point to the important, but so far unexamined role of an organization’s management accountants and their skills for translating big data into high-quality decisions.

The present study highlights the importance of an organization’s human skills in creating value out of big data. In particular, the findings imply that management accountants may need to increasingly draw on data analytics skills to make the most out of big data for their employers.

This study is among the first, to the best of the authors’ knowledge, to provide empirical proof of the relevance of an organization’s management accountants and their data analytics skills for reaching desirable firm-level outcomes. In addition, this study thus adds to the further advancement of the knowledge-based view by providing evidence that in contemporary big-data environments, interactions between tacit and explicit knowledge seem crucial for driving desirable firm-level outcomes.