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This paper aims to discuss recent criticism related to partial least squares structural equation modeling (PLS-SEM).

Using a combination of literature reviews, empirical examples, and simulation evidence, this research demonstrates that critical accounts of PLS-SEM paint an overly negative picture of PLS-SEM’s capabilities.

Criticisms of PLS-SEM often generalize from boundary conditions with little practical relevance to the method’s general performance, and disregard the metrics and analyses (e.g., Type I error assessment) that are important when assessing the method’s efficacy.

We believe the alleged “fallacies” and “untold facts” have already been addressed in prior research and that the discussion should shift toward constructive avenues by exploring future research areas that are relevant to PLS-SEM applications.

All statistical methods, including PLS-SEM, have strengths and weaknesses. Researchers need to consider established guidelines and recent advancements when using the method, especially given the fast pace of developments in the field.

This research addresses criticisms of PLS-SEM and offers researchers, reviewers, and journal editors a more constructive view of its capabilities.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

This study aims to explore and segment consumer preferences for electric and hybrid vehicles in Germany, Sweden, the Netherlands and Turkey, focusing on understanding the various factors that influence consumer decisions in these markets.

Using latent class analysis (LCA) on data collected through online surveys and discrete choice experiments, this research categorizes consumers into distinct segments. The approach allows for a nuanced understanding of how various factors such as income level, fuel cost, age, CO₂ emissions, purchase price, vehicle range, policy policies and environmental concerns interact with shape consumer preferences.

The analysis uncovers significant heterogeneity in consumer preferences for electric and hybrid vehicles across Germany, Sweden, the Netherlands and Turkey, revealing four key segments: “Eco-Driven Innovators,” “Value-Focused Pragmatists,” “Tech-Savvy Early Adopters” and “Reluctant Traditionalists.” “Eco-Driven Innovators” prioritize environmental benefits and are less sensitive to price, demonstrating a strong inclination toward vehicle CO₂ emissions and policy policies. “Value-Focused Pragmatists” weigh economic factors heavily, showing a sharp interest in fuel costs and purchase prices but are open to considering electric and hybrid vehicles if they present clear long-term savings. Technology-savvy early adopters are attracted by the latest technological advancements in vehicles, regardless of the type, and are motivated by factors beyond just environmental concerns or cost savings. Lastly, “Reluctant Traditionalists” exhibit minimal interest in electric and hybrid vehicles due to concerns over charging infrastructure and upfront costs. This detailed segmentation illustrates the diverse motivations and barriers influencing consumer choices, from governmental policies and environmental concerns to individual financial considerations and technological appeal.

This study stands out for its pioneering application of LCA to dissect the complexity of consumer preferences for electric and hybrid vehicles, a methodological approach not widely used in this research domain. Using LCA, the authors are able to uncover nuanced consumer segments, each with distinct preferences and motivations, providing a depth of insight into market dynamics that traditional analysis methods may overlook. This approach enables a more granular understanding of how diverse factors – ranging from environmental concerns to economic considerations and technological attributes – interact to shape consumer choices in different countries. The findings not only fill a critical gap in the existing literature by mapping the intricate landscape of consumer preferences, but also offer a novel perspective on strategizing market interventions. Therefore, the application of LCA enriches the discourse on sustainable transportation, offering stakeholders, manufacturers, policymakers and researchers – a refined toolkit for navigating the evolving market dynamics and fostering the adoption of electric and hybrid vehicles.

The research goal is to summarize the insights from an investigation of the higher education institutes (HEIs) and university's educational services promotion strategy, which incorporates social media as a medium for keeping in touch with important people throughout time. The study centered on the impact of promotional efforts done by higher education Institutes (HEIs) on social media on students’ decisions for their selection of HEIs and universities as well as the study focus factors that influence the students' decisions. In the third quarter of 2022, based on a carefully chosen sample, researchers used an internet questionnaire to conduct an empirical study. The assessment of the outcomes focused on identifying the significant aspects and their significance in the marketing endeavours conducted on social media platforms, which serve as predictors of student decision-making. Three important predictors Social Media Engagement, Content Contribution, and Stakeholders Review were identified and their significant impact on social media marketing by HEI are hypothesized and tested. All the study variables confirm the existence of a significant relationship with the dependent variable. The study concluded that these factors were identified as significant influences on the choice of study and higher education institution. Gaining new followers, prominence content display and stakeholders' feedback builds long-lasting linkages with the immediate environment. As a foundation for creating successful social media marketing strategies for higher education institutions, this research is useful for marketers since it elucidates the dynamics of the market and the habits of potential pupils.

Large supermarket chains are adopting customer-service robots to improve service delivery in physical stores. Successful deployment of these robots depends on shoppers' willingness to interact with them, requiring an understanding of influencing factors. This study, grounded in the Cognitive-Affective-Normative (CAN) theory, seeks to systematically explore the factors influencing Gen Z shoppers' willingness to interact with customer-service robots.

A hybrid approach combining Structural Equation Modeling (SEM) and Necessary Condition Analysis (NCA) was employed to analyze survey data collected from 945 Gen Zs in the Czech Republic.

The results from SEM highlight significant cognitive, normative, and affective factors that influence the intention of Gen Z shoppers to interact with a customer-service robot. Specifically, cognitive factors such as effort and performance expectancy, along with normative factors like subjective norms, emerged as critical determinants. Furthermore, affective factors such as technology anxiety and positive emotions significantly influence users' readiness to use customer-service robots for service requests. The study also underscores that positive emotions, effort expectancy, performance expectancy, and subjective norms are vital prerequisites for interacting with customer-service robots.

The originality of this work lies in its two significant contributions to the burgeoning field of SRs in retail literature. First, it extends the CAN theory to the context of SRs among Gen Z shoppers in Czechia, thereby enriching the existing literature on SRs in retail. Second, by employing a hybrid analytical approach, our research offers both empirical and methodological advancements, providing rigorous insights crucial for enhancing the understanding of the pivotal factors influencing shoppers' interactions with SRs in physical store environments.

After completion of the case study, the students will be able to[1] review the industry analysis using Porter’s five forces and strength, weakness, opportunities, threats framework and understand how a firm can achieve a competitive advantage, analyze the stakeholder theory and the salience of stakeholder mapping for enterprises with large number of stakeholders, apply the Mendelow framework of stakeholder mapping in this context and integrate it with stakeholder engagement for small enterprises and examine and evaluate how new age enterprises can engage better with stakeholders to provide a higher value creation.

Ayushi Srivastava started her enterprise, Beeyond Foods, in early 2021 with the aim to provide unadulterated, raw honey to consumers. She also wanted to help the beekeeping community by providing the beekeepers with a fair price for the procurement of honey from the bee hives. Beeyond Foods was a small enterprise in India that sold two variants of honey to consumers. The first variant was sourced from the Himalayan region of India, whereas the second was sourced from the Western Ghats of India. The primary distribution channel was trade fairs, where Srivastava would assemble her stall and sell honey to potential customers. Furthermore, a part of the sales was also driven by an electronic channel, which was through the company website. Customers could place their orders, and the honey would directly be delivered to their homes. With a successful start to the business, Srivastava was interested to scale her business and reach more customers. However, she was mindful that there were multiple stakeholders involved in the business. Srivastava had to study the values and needs of each stakeholder, while simultaneously formulate a strategy to expand her reach. This case study is designed to teach the concept of stakeholder value creation for small business enterprises.

This case study is well suited for an entrepreneurship and strategy course at the postgraduate (Master of Business Administration) level. This case study can also be taught in a marketing course.

Teaching notes are available for educators only.

CSS3: Entrepreneurship.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

Disruptive events caused by cyber incidents, such as supply chain (SC) cyber incidents, can affect firms’ SC operations on a large scale, causing disruptions in material, information and financial flows and impacting the availability, integrity and confidentiality of SC assets. While SC resilience (SCRES) research has received much attention in recent years, the purpose of this study is to investigate specific capabilities for building SCRES to cyber risks. Based on a nuanced understanding of SC cyber risk characteristics, this study explores how to build SC cyber resilience (SCCR) using the perspective of dynamic capability (DC) theory.

Based on 79 in-depth interviews, this qualitative study examines 28 firms representing 4 SCs in Central Europe. The researchers interpret data from semistructured interviews and secondary data using the DC perspective, which covers sensing, seizing and transforming.

The authors identify SCRES capabilities, in general, and SCCR-specific capabilities that form the basis for the realignment of DCs for addressing cyber risks in SCs. The authors argue that SCRES capabilities should, in general, be combined with specific capabilities for SCCR to deal with SC cyber risks. Based on these findings, 10 propositions for future research are provided.

Practitioners should collaborate specifically to address cyber threats and risks in SCs, integrate new SC partners and use new approaches. Furthermore, this study shows that cyber risks need to be treated differently from traditional SC risks.

This empirical study enriches the SC management literature by examining SCRES to cyber risks through the insightful lens of DCs. It identifies DCs for building SCCR, makes several managerial contributions and is among the few that apply the DC approach to address specific SC risks.

Small retail stores in the luxury market face significant challenges due to fluctuations in market demand. This task turns challenging as it requires effectively coordinating and translating customer needs into specific requirements that align with retail goals and available resources. However, limited empirical research exists investigating how managers can address service value and quality attributes in small retail stores. This article aims to bridge this gap by investigating the role of quality function deployment (QFD) in improving market and quality requirements management in small retail stores.

Based on the case study, a customer survey was initially conducted to gather information on critical characteristics valued in the luxury retail segment. QFD was used to assist the company in identifying and prioritizing key quality attributes to meet customer requirements effectively.

The findings demonstrate that implementing QFD in small luxury retail stores empowers managers to identify previously neglected product and service quality aspects. The article shows that QFD informs organizational adaptations that align with the demands of the retail market, leading to an improved ability to meet customer expectations and enhance customer value through the development of enhanced products and services. The study showcases the efficacy of the tested methodology in effectively capturing and prioritizing both tangible and intangible customer needs in retail.

Findings offer valuable insights to retail managers of small luxury stores, providing actionable market-oriented strategies. By implementing the recommended practices, managers can improve the store’s competitiveness and better cater to the customer base.

This study contributes to bridging persistent knowledge gaps by addressing the unique context of small luxury retail stores and introducing the application of QFD in this setting. The insights gained from this research are relevant to both retailing and quality management literature. Considering the growing prevalence of transformations in the retail industry, the study provides practical implications for retail managers in effectively navigating these changes.

Given the contradictory findings of standardization/adaptation of marketing strategy in explaining export performance in the extant research, this study aims to examine the contingent effects of managerial ties and born global orientation in the standardized advertising-export performance conceptualization.

The study used two-respondent method in the survey research by a sample of 155 exporting firms operating in the industrial marketing based in Australia and New Zealand and applied hierarchical regression analysis to test the hypotheses.

The findings demonstrate that standardized advertising has a significant effect on export performance and this relationship is positively moderated by business ties. Such effect is particularly enhanced for born global firms (than nonborn global firms). However, political ties negatively influence the impact of standardized advertising on performance and such effect is stronger for born global firms.

A broader perspective of contingent variables should be included to examine the underlying relationship between standardized advertising and export performance in capturing the dynamism in international marketing contexts, such as institutional frameworks or sociocultural environments in host countries.

Standardized advertising is critical for born global firms’ export performance as it can increase efficiency and speed up internationalization processes. Such positive impact of standardized advertising on export performance is further enhanced if born global firms allocate resources to develop strong business ties with host country partners instead of building political ties with host country governments, because smooth business networking can facilitate standardized advertising on industrial marketing, yet justifiable political relations require intricate negotiations that often prolong internationalization progress.

This study incorporates managerial ties and born global orientation as contingent factors in fixing the theoretic interlock between standardization advertising strategy and export firm performance.