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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.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

The partial least squares structural equation modeling (PLS-SEM) approach for construction management (CM) scholars has become the preferred approach for its capability of assessing the complex relationship and relaxed normality and sample size assumptions. This paper systematically maps the structure of knowledge about PLS-SEM in CM using bibliometric analysis. Also, the study employs meta-analysis to explore how data and model characteristics, model evaluation and advanced modeling techniques have been utilized in the CM domain.

This study integrated two methods: bibliometric analysis on a sample of 211 articles identified using the PRISMA framework and meta-analysis on 163 articles identified based on the availability of full-length articles and relevant information.

The results revealed the leading knowledge formation entities (countries, institutions, authors, sources and documents). Also, the study employs full content analysis to identify six research themes, and meta-analysis is used to explore the use of PLS-SEM based on the following criteria: (1) reasons for using PLS-SEM in CM, (2) data characteristics, (3) model characteristics and evaluation and (4) use of advanced modeling and analysis techniques. Further, the study uses regression analysis and identifies “advanced modeling and analysis techniques” as the critical feature responsible for the publication in a journal with high scientific prestige. Finally, the study presented the comprehensive guidelines to be used by construction management scholars who wish to use PLS-SEM in their research work.

To the author’s knowledge, it is the first study of this kind to use PLS-SEM in CM research. This study provides an extensive analysis of the Scopus database and an in-depth review of the data characteristics, model characteristics and use of advanced modeling techniques in CM research.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

The purpose of this study is to use empirical data to examine the hierarchical impact of the Internet of things capability on supply chain integration (SCI), supply chain capability (SCC) and firm performance (FP) in the UK retail industry.

A deductive approach was employed to carry out this research. Structural equation modelling (SEM) was performed using the partial least square method (SmartPLS 3.3.3) to test theoretical predictions which underlie the relationships among Internet of things capability (IoTC), SCI, SCC and FP. Data are collected using an online survey completed by senior executives of 66 large, medium and small firms within the UK retail industry.

The empirical results of this research reveal that IoTC has a significant positive effect on the UK retail industry FP through the mediating role of SCI and SCC.

The research results from this study provide useful management insights for firms within the retail industry into the development of effective strategies for integrating their supply chain alongside the adoption of IoTC into SCI, consequently leading to improvements in FP.

Although previous studies have explored the impact of IoT on FP through the sequential mediating role of SCI and SCC, few have explored the impact of the IoT capability (IoTC) on FP through sequential mediators, i.e. SCI and SCC. This study examines the relationship between IoTC, SCI, SCC and FP in the UK retail industry supply chain to address this knowledge gap. Moreover, this study examines the effects of IoTC on FP by applying partial least square (PLS)-SEM techniques. Testing the sequential mediating role of SCI and SCI is undertaken, and the relationships among IoT-enabled SCI and SCC is analysed to improve FP. The robustness check's result through PLSpredict analysis also confirms the power of the model proposed in this study.

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.

Indian construction firms are falling behind in the use of digital technology in the workplace, and this study aims to give a framework and assess the role of enablers in the implementation and continuing digitalization of the Indian construction sector.

An exploratory qualitative research technique is used in this article, and multiple detailed interviews and surveys are done with professionals from the industry and academia. To conclude the significance and relevance of the different constructs and indicators, the partial least square-structural equation modeling (PLS-SEM) approach is used.

Barriers are essential enablers for effective implementation, while success factors are important drivers for the successful continuance of digitalization in the construction sector. However, stakeholders' perceived benefit has a substantial role in both implementation and continuance.

In this research paper, the scope of this investigation for a generalized exploratory study is restricted to construction firms within India. Further, a rigorous longitudinal study may also be performed to examine the subjectivity of the responses in order to ensure digital continuation. This study identifies limited manifest indicators. Additional indications, however, may be included based on the other company's resources, structure and geographic location.

The study's findings have two implications. In the beginning, it gives a direction to the construction sector by highlighting the framework in which implementation and continuance both should have to be executed, and this is the critical area for the successful continuance of digitalization in construction. Second, the research shows that the digitalization process is similar to the adoption of innovation, in which the deployment and persistent use of the new technology are important for facilitating the transformation.

In two respects, the study is distinctive. To begin, this is one of the limited efforts to comprehend digitalization from the Indian perspective. Second, the study reveals that the PLS-SEM approach can be effectively used in the developing subject of the construction digitalization concept.

This study, grounded in the SOR theory, aims to enrich the understanding of customer citizenship behaviour in omnichannel fashion retail by examining how different customer experiences enhance customer engagement and how that engagement leads to customer citizenship behaviour. The influence of return policies on the relationship between customer engagement and customer citizenship behaviour was also examined.

Partial least squares structural equation modelling (PLS-SEM) is used to examine the framework of the proposed study with data collected through a survey (n = 251) to examine the opinions of the respondents about the variables mentioned. The authors also assessed the proposed framework using predictive power assessment using PLS predict.

The study results reveal that customers’ experiences of integration and flexibility in omnichannel retail are positively associated with their engagement. However, customer experiences of connectivity, consistency and personalization do not appear to affect customer engagement significantly in omnichannel retail. The return policy positively moderates the relationship between customer engagement and customer citizenship behaviour in the omnichannel fashion retail context. Predictive power assessment shows that the proposed model has high prediction accuracy.

This study contributes to the marketing literature by investigating different dimensions of consumer experience collectively and its impact on customer engagement and citizenship behaviour. Furthermore, the study contributes to omnichannel retail in fashion industry by testing the return policy as a moderator variable on the relationship between customer engagement and citizenship behaviour.

Este estudio, basado en la teoría SOR, enriquece la comprensión del comportamiento cívico del cliente en el comercio minorista de moda omnicanal examinando cómo las diferentes experiencias del cliente mejoran el compromiso de éste y cómo dicho compromiso conduce al comportamiento cívico del cliente. También se examina la influencia de las políticas de devolución en la relación entre el compromiso del cliente y el comportamiento ciudadano del cliente.

Se utilizó la modelización PLS-SEM para examinar el marco del estudio propuesto con datos recogidos mediante una encuesta (n = 251) para examinar las opiniones de los encuestados sobre las variables mencionadas. Los autores también evaluaron el marco propuesto mediante una evaluación del poder predictivo utilizando la predicción PLS.

Los resultados revelan que las experiencias de integración y flexibilidad de los clientes en el comercio minorista omnicanal se asocian positivamente con su compromiso. Sin embargo, las experiencias de los clientes de conectividad, coherencia y personalización no parecen afectar significativamente al compromiso del cliente en el comercio minorista omnicanal. La política de devoluciones modera positivamente la relación entre el compromiso del cliente y el comportamiento ciudadano en el contexto del comercio minorista de moda omnicanal. La evaluación del poder predictivo mostró que el modelo propuesto tenía una alta precisión de predicción.

El estudio contribuye a la literatura de marketing investigando colectivamente diferentes dimensiones de la experiencia del consumidor y su impacto en el compromiso del cliente y el comportamiento ciudadano. Además, este estudio contribuye a la venta minorista omnicanal en la industria de la moda al probar la política de devoluciones como variable moderadora de la relación entre el compromiso del cliente y el comportamiento ciudadano.

本研究以 SOR 理论为基础, 通过研究不同的顾客体验如何提高顾客参与度, 以及顾客参与度如何推动顾客公民行为, 丰富了对全渠道时尚零售中顾客公民行为的理解。研究还探讨了退货政策对顾客参与和顾客公民行为之间关系的影响。

本文采用 PLS-SEM 模型来检验拟议的研究框架, 并通过调查（n = 251）收集数据, 以检验受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

通过调查（n = 251）收集的数据, 使用 PLS-SEM 模型来研究拟议的研究框架, 以考察受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

研究结果表明, 顾客在全渠道零售中对整合性和灵活性的体验与他们的参与度呈正相关。然而, 顾客在连通性、一致性和个性化方面的体验似乎并未对顾客参与全渠道零售产生显著影响。退货政策对全渠道时尚零售中顾客参与和公民行为之间的关系起到了积极的调节作用。 预测能力评估表明, 所提出的模型具有较高的预测准确性。

本研究通过对消费者体验的不同维度及其对顾客参与和公民行为的影响进行综合研究, 为营销文献做出了贡献。此外, 本研究通过检验退货政策作为顾客参与和公民行为之间关系的调节变量, 为时尚行业的全渠道零售做出了贡献。

This study examines the influence of consumer skepticism on cause-related marketing (CRM) campaign participation intentions of Generation Z consumers from emerging market perspective. This study was undertaken due to the paucity of relevant literature in the public domain to directly investigate whether and how consumers' skepticism affects CRM participation intentions, specifically in the luxury retailing context.

A survey was conducted among 552 Generation Z consumers and path analysis was used to examine the direct and indirect effects of skepticism. The mediation and moderation analysis was used to explore and test the authors' hypotheses via partial least squares structural equation modeling (PLS SEM).

The authors' findings provide empirical evidence that corporate social responsibility, religiosity and cause involvement positively affects consumer participation intentions, and this link is also established indirectly through skepticism toward the CRM campaign. These findings provide novel theoretical contributions by establishing skepticism's complex role in determining the CRM participation intention in the Generation Z consumers' context. This study further demonstrates the moderating effect of gender and luxury store format on consumer skepticism and CRM participation intentions.

The Generation z group will represent a quarter of the Asia–Pacific region's population by 2025. However, little is known about Generation z consumers' CRM participation intentions. This research would help practitioners, including luxury retailers, CRM managers and advertising professionals, to effectively design CRM campaigns. The paper contributes by highlighting the theoretical implications and managerial implications based on the current findings in the emerging market context.

To further improve the branding strategies between single-brand-retailers and multi-brand-retailers, the paper investigates the influence of multiple manufacturer brand images on retailer brand image. It considers the moderating role of the number of offered manufacturer brands.

The research is conducted in the automotive retail context. Based on an online survey (383 respondents), a Partial-Least Squares Modeling, estimated using SmartPLS 3 and a classic partial least squares structural equation modeling (PLS-SEM) algorithm, is used to validate the hypotheses.

The results reveal that manufacturer brands did not influence the retailer's brand image in all cases since it is only influenced by the manufacturer brand when the retailer offers only one manufacturer brand.

For retailers offering only one manufacturer brand, the most extensive possible adoption of the corporate identity (CI) specifications prescribed by the manufacturer brands is the prerequisite for a positive image effect. Retailers offering more than one manufacturer brand should create their image based on the retailer's identity. In this context, it is essential to position the retailer brand independently in the market.

This is the first study focuses on retailers with a small or limited number of offered manufacturer brands to answer the question of whether the number of provided manufacturer brands moderates the impact of manufacturer brand images on the retailer's brand image.