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Driven by the disruptive effects of the Covid-19 pandemic, the ongoing debate about the international location of firms' manufacturing activities has increasingly highlighted the specific benefits and costs of near-shoring versus far-shoring. However, the effects of near-shoring versus far-shoring on customer perceived quality and purchase intention have not been examined. Thus, this study aims to develop a conceptual model and provide new evidence to fill this gap. In particular, the study explores the roles of brand familiarity and corporate social responsibility (CSR) to explain the different levels of perceived quality and purchase intention in relation to near-shoring versus far-shoring.

This study includes two analyses of data collected from a sample of Italian customers. The first analysis consists of a 2 (high/low brand familiarity) × 3 (domestic insourcing, near-shoring, far-shoring) factorial design, and data are assessed via analyses of variance (ANOVA). The second analysis evaluates the suggested model in the two scenarios (near-shoring and far-shoring) via partial least squares–structural equation modelling (PLS-SEM) multigroup analysis.

Results showed that customer perceived quality and purchase intention were significantly higher for near-shoring than for far-shoring, but only when brand familiarity was low. No significant difference was found for participants with a high level of brand familiarity. In addition, the level of a brand's pre-offshoring perceived CSR was negatively related to perceived quality, and this was conceptually justified by the CSR-washing effect. Again, this effect was found only when brand familiarity was low.

The findings contribute to advancing the current understanding of the multiple effects of the offshoring decision and clarify that near-shoring and far-shoring have different effects for customers with low brand familiarity. The findings also emphasise that the far-shoring decision can elicit the perception of decoupling between the firm's CSR claims and CSR actions, thus decreasing perceived quality.

This study provides managers with additional inputs to make more informed decisions regarding offshoring. While the post-pandemic scenario seems to favour near-reshoring over far-shoring due to agility considerations, this study also provides additional evidence of the superiority of near-reshoring from the customer's perspective.

This is the first study to examine and prove the differential effects of near-shoring versus far-shoring on the customer's perceptions and behaviours.

We review and extend the arguments of Chen, Mathieu and Bliese by providing some foundational and guiding questions to assist researchers in multi-level construct validation. First, we suggest that all multi-level researchers need to gain a firm understanding of the difference between individual and collective constructs. Second, we make a distinction between collective constructs that describe the collection of individuals within the group vs. those that describe the collective as a whole. This distinction provides a framework to sort the various compositional models discussed by Chen et al. into two broad categories. After discussing these two questions, we then develop a decision tree that guides researchers through a series of questions and ultimately helps researchers to identify the appropriate compositional model.

The purpose of this paper is to examine the structural relationships among explorative learning strategy, improvisational creativity, compositional creativity, and innovation in information and communication technology small- and medium-sized enterprises (ICT-SMEs).

In total, 213 valid questionnaires from SMEs’ top management positions were evaluated to investigate the proposed model of the research empirically. As a methodological approach, partial least square (PLS) path modeling approach, a variance-based structural equation modeling was employed.

The statistical results imply that explorative learning has a positive impact on improvisational creativity and innovation while improvisational creativity has a positive influence on compositional creativity and innovation as well. Compositional creativity and innovation are also positively associated. Surprisingly, improvisational creativity mediates the relationship between explorative learning and innovation. Furthermore, PLS-multi group analysis reveals that heterogeneity exists in the collected data and number of employees is a moderating variable. The results of the research indicate that companies with number of employees between 51 and 100 are more creative and innovative in comparison with other groups. On the other hand, the positive relationship between explorative learning and compositional creativity was not supported in this research.

This study is one of the few research works in the realm of examining the structural relationship among explorative learning strategy, improvisational creativity, compositional creativity, and innovation in ICT-SMEs, regarding the number of employees as a moderating variable.

The purpose of this paper is to propose a model of competitiveness for small and medium-sized enterprises (SMEs) by investigating the structural relationship between organizational structure, knowledge quality (KQ) dimensions, improvisational creativity, compositional creativity and innovation in an emerging market – Malaysia – grounding in sense-making and organizational improvisational theories.

A total of 358 valid questionnaires administered among SMEs’ top management were used in examining the measurement model and structural relationship between latent constructs using partial least squares (PLS) path-modelling approach.

The findings indicate that a flat organizational structure influences business entities’ sense-making activities in the way they realize the intrinsic value of knowledge (intrinsic KQ) and take action to apply the organizational knowledge (actionable KQ). These sense-making activities are also conducive to SMEs’ improvisational creativity, compositional creativity and innovative capabilities. All KQ dimensions are positively interrelated, thus supporting sense-making theory.

A sustainable competitive advantage for SMEs requires a setting that is based on a lean, decentralized and cooperative organizational structure that shapes organizational KQ. As a contribution to the literature, accessibility KQ is introduced as a KQ dimension. Even though previous research was unclear on the reflectiveness/formativeness of KQ, by applying confirmatory tetrad analysis-PLS, this study empirically supports that KQ is a formative construct.

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

This study aims to offer insight into the applications of multilevel confirmatory factor analysis (MCFA) within organizational behavior (OB) studies, specifically when using macro-level variables. The authors used the case of a scale measuring collective organizational engagement (COE) to demonstrate the advantage of using MCFA over single-level confirmatory factor analysis (CFA).

The authors used nine referent-shift items to measure the dimensions of physical, cognitive and emotional COE. MCFA and aggregated single-level CFA were conducted on the same data using Mplus V. 8.7, and the authors compared standardized parameters from the two techniques.

The results indicate a three-factor model of collective engagement with CFA and MCFA. Stronger item loadings, factor correlations and composite reliability were found in the MCFA within-level model compared to aggregated CFA model. MCFA also supported an alternate one-factor-between-three-factors-within model of COE.

This study demonstrates the application of MCFA with a compositional construct and compares MCFA to mean-aggregated single-level CFA. It presents a case for OB researchers to apply MCFA to compositional constructs as a best methodological practice.

A total of 210 valid paper-and-pencil questionnaires were received from fast-moving consumer goods/small and medium-sized enterprises (FMCG-SMEs) to empirically test the proposed model. Structural equation modelling approach was performed to assess the model fit, measurement and structural models for exogenous and endogenous constructs, and test of nonlinearity.

In the hyper-competitive world, while the essence of strategy making is often focussed on environmental and market-based analysis or the structure of the market, the important role of resources and capabilities in determining firm performance and overall strategy formulation within SMEs begs attention. Grounded in the resource-based view (RBV) of the firm, organisational improvisation theory and componential theory of creativity, the purpose of this research is to look beyond the determinants of creativity, innovation and proposes a theoretical model investigating organisations formative performance in strategy formulation.

The results imply that intrinsic motivation, extrinsic motivation, creativity-related processes and expertise as the firm's capabilities positively influence improvisational creativity, and creativity-related processes and expertise also positively impact on compositional creativity. Surprisingly, intrinsic and extrinsic motivations are not conducive to compositional creativity, and the relationships between extrinsic motivation and improvisational creativity as well as improvisational creativity and performance are nonlinear. Furthermore, both improvisational creativity and compositional creativity are found to be predictors of innovation in FMCG-SMEs.

Thus, organisations and specifically FMCG-SMEs can increase the level of improvisational creativity if they formulate strategies to motivate employees both intrinsically and extrinsically, and further, they can boost the level of compositional creativity in their companies through hiring and nurturing experts.

Less attention has been paid to motivation, creativity, innovation, performance and strategy linkages as the prominent source of competitive advantages among FMCG-SMEs, especially in developing countries. Theoretically, through introducing extrinsic motivation as the predictors of improvisational creativity and innovation, from strategic management perspectives, the empirical findings of this research illustrate that resources and capabilities (RBV) lead to improved competitive performance within the FMCG-SMEs. This study also provides empirical evidence for the nonlinear nature of the relationship between motivation and creativity.

Team cognition is known to be an important predictor of team process and performance. DeChurch and Mesmer-Magnus (2010) reported the results of an extensive meta-analytic examination into the role of team cognition in team process and performance, and documented the unique contribution of team cognition to these outcomes while controlling for the motivational dynamics of the team. Research on team cognition has exploded since the publication of DeChurch and Mesmer-Magnus’ meta-analysis, which raises the question: to what extent do the effect sizes reported in their 2010 meta-analysis still hold with the inclusion of newly published research? The paper aims to discuss this issue.

The authors updated DeChurch and Mesmer-Magnus’ meta-analytic database with newly published studies, nearly doubling its size, and reran their original analyses examining the role of team cognition in team process and performance.

Overall, results show consistent effects for team cognition in team process and performance. However, whereas originally compilational cognition was more strongly related to both team process and team performance than was compositional cognition, in the updated database, compilational cognition is more strongly related to team process and compositional cognition is more strongly related to team performance.

Meta-analyses are only as generalizable as the databases they are comprised of. Periodic updates are necessary to incorporate newly published studies and confirm that prior findings still hold. This study confirms that the findings of DeChurch and Mesmer-Magnus’ (2010) team cognition meta-analysis continue to generalize to today’s teams.

Organizational researchers have become increasingly interested in multi-level constructs – that is, constructs that are meaningful at multiple levels of analysis. However, despite the plethora of theoretical and empirical work on multi-level topics, explicit frameworks for validation of multi-level constructs have yet to be fully developed. Moreover, available principles for conducting construct validation assume that the construct resides at a single level of analysis. We propose a five-step framework for conceptualizing and testing multi-level constructs by integrating principles of construct validation with recent advancements in multi-level theory, research, and methodology. The utility of the framework is illustrated using theoretical and empirical examples.

This article presents a comprehensive and qualitative review of how levels of analysis issues have been addressed in the diversity and demography literature. More than 180 conceptual and empirical publications (i.e. book chapters and journal articles) in this field are reviewed and coded regarding the specific incorporation of levels of analysis in theory and hypothesis formulation, representation of levels of analysis in measurement of constructs and variables, appropriateness of data-analytic techniques given the explicit or implied levels of analysis, and alignment between levels of analysis in theory and data in regard to drawing inferences and conclusions. Although the body of diversity and demography literature continues to grow, levels of analysis issues are rarely considered. Only a few reviewed studies address levels of analysis issues in theory development, and no reviewed studies employ appropriate multi-level data analytic techniques. Implications for future research are discussed, and recommendations for incorporating levels of analysis into diversity and demography research are provided.