A Trail Guide to Publishing Success: Tips on Writing Influential Conceptual, Qualitative, and Survey Research

Abstract

P ublishing in top journals is difficult. Common challenges undermine authors' attempts to explain and influence their discipline's understanding and practice. We identify and describe these roadblocks to publishing success. We also benchmark best practice in management, marketing, and supply chain journals to provide a trail guide for writing-and publishing-influential conceptual, qualitative, and survey research. Given equifinality in research, our trail guide should not be viewed as the only way to craft excellent, influential research. However, if we agree on the basics, we can (1) increase consistency in the review process, (2) reduce publication cycles, and (3) begin to roll back the length of articles.

The role of Big Data in explaining disaster resilience in supply chains for sustainability

“…Appendix B clearly shows the standardized factor loadings of each indicator (!0.5), the composite reliability (SCR) (!0.7) and average variance extracted (AVE) (!0.5). The results clearly support the convergent validity test as suggested by scholars (see Fornell and Larcker, 1981;Fawcett et al, 2014). For discriminant validity we checked the squared root of AVE measured for each of the constructs, and it was found to be greater than the correlation coefficients between each pair of constructs in the same column.…”

Antecedents of Resilient Supply Chains: An Empirical Study

“…Next, we assessed two types of validity: convergent and discriminant [73]. As shown in Table 3, items load on the intended constructs with standardized loadings greater than 0.5, the scale composite reliability (SCR) greater than 0.7 and the average variance extracted (AVE) greater than 0.5.…”

“…Hence, we can argue that there is sufficient evidence for convergent validity. Fawcett and colleagues [73] noted that for discriminant validity, all the items should have higher loadings on their assigned constructs than on any other constructs. Furthermore, the mean shared variance should be below 0.50.…”

Upstream supply chain visibility and complexity effect on focal company’s sustainable performance: Indian manufacturers’ perspective

“…We compared the responses of early and late waves of returned survey based on assumption that the opinions of the late respondents are representative of the opinions of the non-respondents (see Armstrong and Overton, 1977;Lambert and Harrington, 1990). However, Fawcett et al (2014) noted that comparing early to late respondents may not be a strong test of nonresponse bias. Hence, we also adopted alternative techniques (see Fawcett et al 2014) and compared the demographics of the late respondents via a Dun & Bradstreet database and further followed up by making a phone call to increase the confidence level of the late respondents.…”

“…However, Fawcett et al (2014) noted that comparing early to late respondents may not be a strong test of nonresponse bias. Hence, we also adopted alternative techniques (see Fawcett et al 2014) and compared the demographics of the late respondents via a Dun & Bradstreet database and further followed up by making a phone call to increase the confidence level of the late respondents. The t-tests yielded no statistically significant differences between early-wave (160 responses) and late-wave (152 responses), suggesting that non-response bias was not a problem.…”