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The purpose of this paper is to use the job demands-resources model to investigate intra-individual engagement-burnout profiles, and demands-resources profiles.

A representative sample of the US workforce was surveyed online. Latent profile analysis (LPA) and configural frequency analysis examined intra-individual profiles and their inter-relations.

A negative inter-individual correlation between engagement and burnout suggested that burnout tends to be lower when engagement is high, but intra-individual analyses identified both aligned engagement-burnout profiles (high, moderate, and low on both variables), and discrepant profiles (high engagement – low burnout; high burnout – low engagement). High engagement and burnout co-occurred in 18.8 percent of workers. These workers reported strong mixed (positive and negative) emotions and intended to leave their organization. Another LPA identified three demands-resources profiles: low demands – low resources, but moderate self-efficacy, low workload and bureaucracy demands but moderate information processing demands – high resources, and high demands – high resources. Workers with high engagement – high burnout profiles often reported high demands – high resources profiles. In contrast, workers with high engagement – low burnout profiles often reported profiles of high resources, moderate information processing demands, and low other demands.

This study examined the intersection of intra-individual engagement-burnout profiles and demands-resources profiles. Previous studies examined only one of these sides or relied on inter-individual analyses. Interestingly, many employees appear to be optimally engaged while they are burned-out and considering to leave their jobs. Demands and resources facets were distinguished in the LPA, revealing that some demands were associated with resources and engagement.

This article aims to provide prospective authors guidelines that will hopefully enable them to submit more competitive manuscripts to journals publishing careers research.

Based on their experience as an author, reviewer and editorial team member, the authors identify the main criteria that a quantitative study must meet to be considered for publication in international peer-reviewed journals covering career-related topics. They emphasize the importance of contributing to the careers literature and of designing the study in accordance with the research question.

Manuscripts are rejected because they are insufficiently innovative, and/or because sample, instruments and design are not appropriate to answer the research question at hand. Cross-sectional designs cannot be used to answer questions of mediation but should not be discarded automatically since they can be used to address other types of questions, including questions about nesting, clustering of individuals into subgroups, and to some extent, even causality.

The manuscript provides an insight into the decision-making process of reviewers and editorial board members and includes recommendations on the use of cross-sectional data.

The purpose of this paper is to suggest and empirically test a model that explains employee capabilities from the knowledge‐based perspective. In this model, human capital management practices are employed as a moderator variable.

A valid research instrument was utilized to conduct a survey of 14,769 current employees of a major North American financial services institution. The model was tested by using the partial least squares (PLS) structural equation modeling technique. A thorough analysis of the role of moderator was carried out.

Findings provide support for the proposed model and show that employee capabilities depend on his or her training and development as well as job satisfaction levels. Job satisfaction in turn is affected by training and development, pay satisfaction, supervisor satisfaction, and job insecurity. These relationships are moderated by employee perceptions of human capital management practices. The model exhibits the highest predictive power when the employee perceptions of human capital management practices are also high.

With respect to a moderator analysis, no interaction effects of human capital management policies and other constructs were discovered, and the moderator was referred to as a homologizer that modifies the strength of the relationships among constructs through an error term. It was discovered that PLS and moderated multiple regression (MMR) produced very similar structural relationships when a moderator was employed.

The findings may be utilized by knowledge management, organizational behavior, and human resources practitioners interested in the development of strong employee capabilities.

This paper represents one of the first documented attempts to utilize human capital management practices as a moderator in organizational models.

Data mining has been a popular research area in the past decades. Many researchers study data-mining theories, methods, applications and trends; however, there are very few studies on data-mining-related topics in social media. This paper aims to explore the topics related to data mining based on the data collected from Wikipedia.

In total, 402 data-mining-related articles were obtained from Wikipedia. These articles were manually classified into several categories by the coding method. Each category formed an article-term matrix. These matrices were analysed and visualized by the self-organizing map approach. Several clusters were observed in each category. Finally, the topics of these clusters were extracted by content analysis.

The articles obtained were classified into six categories: applications, foundation and concepts, methodologies, organizations, related fields and topics and technology support. Business, biology and security were the three prominent topics of the applications category. The technologies supporting data mining were software, systems, databases, programming languages and so forth. The general public was more interested in data-mining organizations than the researchers. They also focused on the applications of data mining in business more than in other fields.

This study will help researchers gain insight into the general public’s perceptions of data mining and discover the gap between the general public and themselves. It will assist researchers in finding new techniques and methods which will potentially provide them with new data-mining methods and research topics.

This paper aims to advance a configural asymmetric theory of the complex antecedents to hospitality employee happiness-at-work and managers’ assessments of employees’ quality of work performance. The study transcends variable and case-level analyses to go beyond prior statistical findings of small-to-medium effect sizes of happiness–performance relationships; the study here identifies antecedent paths involving high-versus-low happy employees associating with high-versus-low managers’ assessments of these employees’ performances.

The study merges data from surveys of employees (n = 247) and surveys completed by their managers (n = 43) and by using qualitative comparative analysis via the software program, fsQCA.com. The study analyzes data from Janfusan Fancyworld, the largest (in revenues and number of employees) tourism business group in Taiwan; Janfusan Fancyworld includes tourist hotels, amusement parks, restaurants and additional firms in related service sectors.

The findings support the four tenets of configural analysis and theory construction: recognize equifinality of different solutions for the same outcome, test for asymmetric solutions, test for causal asymmetric outcomes for very high versus very low happiness and work performance and embrace complexity.

Additional research in other firms and additional countries is necessary to confirm the usefulness of examining algorithms for predicting very high (low) happiness and very high (low) quality of work performance. The implications are substantial that configural theory and research will resolve perplexing happiness–performance conundrums.

The study provides useful case-level algorithms involving employees’ demographic characteristics and their assessments of work facet-specifics which are useful for explaining very high happiness-at-work and high quality of work performance (as assessed by managers) – as well as algorithms explaining very low happiness and very low quality of work performance.

The study is the first to propose and test the tenets of configural theory in the context of hospitality frontline service employees’ happiness-at-work and managers’ assessments of these employees’ quality of work performances.

The purpose of this paper is to explore how external pressures, internal capability and transaction attributes of logistics outsourcing synergically influence the extent of asset-based and non-asset-based logistics outsourcing.

Based on the data surveyed from 250 manufacturing companies in China, this study employed fuzzy-set qualitative comparative analysis (fsQCA) to deduce multiple configurations for logistics outsourcing decisions.

The results suggest that asset-based logistics outsourcing is primarily driven by external imitation pressures or internal demands for logistics technologies, while non-asset-based logistics outsourcing is mainly driven by the demands for external management-based logistics services. Asset specificity plays a positive role in promoting both asset-based and non-asset-based logistics outsourcing. The requirement for third-party logistics (3PL) management capability depends on the outsourcing types and outsourcing causes.

This study provides guidance to practitioners for them to make outsourcing decisions. It suggests that asset-based logistics outsourcing is more appropriate when there are high external imitation pressures or more internal logistics demands, while non-asset-based logistics outsourcing should be used only when a firm needs management-based logistics services. Besides, 3PL users are suggested to outsource their logistics when their 3PL providers are required to make specific investments. In addition, managers should carefully evaluate firms’ capabilities in managing outsourcing relationships.

Previous studies largely ignored the interaction effects of a set of factors on logistics outsourcing decisions, and to date, little research empirically examined how outsourcing is driven in terms of different types of outsourcing. Drawing on the institutional theory, dynamic capability view, and transaction cost theory and overarching under the complexity theory, this study examines how institutional, organizational and transactional factors interplay with each other to influence different types of logistics outsourcing (i.e. asset based and non-asset based). Methodologically, the configural analysis (i.e. fsQCA) is applied to explore complex causal configurations that drive logistics outsourcing.

This paper synthesizes the extant feedback literature, focusing on how feedback affects an auditor’s learning, performance, and motivation. Performance feedback is an important component in the auditing environment for ensuring quality control and for developing and coaching staff auditors. However, the literature on feedback in the audit environment is fragmented and limited making it difficult to assess its behavioral effects on auditors. This paper has three main objectives. The first is to review some of the influential research in psychology and management to identify key variables and issues that appear to be critical in the study of behavioral consequences of feedback in organizational settings. The second is to review performance feedback research specifically in auditing to identify the areas previously examined and synthesize the findings. The third is to suggest a variety of future research opportunities that may assist in developing an understanding and knowledge of the behavioral effects of feedback on auditors. The literature analysis has significant implications for audit research and practice. In particular, the analysis provides important insights into understanding who, how, and when performance feedback should be given to improve its effectiveness in the audit environment.

Practitioners and researchers have reached a consensus that supply chain analytics is a strong determinant for desirable organizational outcomes such as supply chain performance and agility. The purpose of this paper is to examine a configural combination (i.e. causal recipes) subsuming supply chain data analytics, firmsize, age and annual sales to predict supply chain agility based on knowledge-based theory.

Survey data (n = 215) were obtained from firms operating in the United Arab Emirates. Consequently, fuzzy sets qualitative comparative analysis (fsQCA) technique was applied to the data to establish causal recipes that are necessary and sufficient to achieve high scores of supply chain agility.

Results from fsQCA support the major tenets of complexity theory that several configural combinations (i.e. supply chain data analytics, firm size, firm age and annual sales) are sufficient and necessary conditions for achieving higher scores of supply chain agility.

This study is first of its kind in understanding the association between supply chain data analytics and agility with fsQCA technique. This research also offers a headway for supply chain managers in identifying configural combinations of antecedents manifesting high scores for supply chain agility. Implications for theory and practice are illustrated as well as future research course.

This paper aims to examine the effects of gender and visit frequency as moderating variables on the relationships among destination perceived quality, tourist satisfaction and word-of-mouth (WOM).

This study incorporated several previous research models to propose a conceptual model that fully explains the relationships among destination perceived quality, tourist satisfaction, visit frequency and WOM. One important thing to consider is whether gender and visit frequency impact on the relationships among these factors. In addition, this study was able to generate measurement items for the dimensions by analyzing specific tourism conditions in Danang City and referring to the scales of these factors in previous studies. Quantitative research was conducted to test the scales of the research model and hypotheses through data collected from 303 domestic tourists.

Structural equation modeling and a multi-group analysis were used to test the hypotheses and the invariance of structural coefficients across groups. The results indicate that destination perceived quality has significant, positive and direct effect on tourist satisfaction; WOM is positively influenced by destination perceived quality and tourist satisfaction; and there is significant relationship between visit frequency and WOM. In particular, when exploring the impact of moderating variables such as gender and visit frequency, this study also found that the impacts of destination perceived quality on WOM are different between genders, and this impact is stronger for female rather than male tourists; and the effect of destination perceived quality on tourist satisfaction is stronger for the first visit than for later visits.

This paper is limited in its ability to gather a larger sample to more generally represent the complete domestic market, as well as in its lack of a comparison of online versus offline WOM effects by gender.

This paper was conducted to have a better understanding of how tourist demographic characteristics such as gender and visit frequency are important contributors that influence the relationships among these three factors. This paper has important implications for marketers and managers of Danang, such as local tourism authorities, commercial association managers, hotel owners, restaurant owners and tour managers working to improve the quality of this destination, and thus better satisfying tourists and competing with other destinations.

The purpose of this paper is to introduce qualitative comparative analysis (QCA) to the field of supply chain management and provide a detailed roadmap that supply chain researchers can utilize when applying this methodology.

Data collection focused on the evaluation of product returns management practices as perceived by business customers who operate in a supplier–customer context. In order to analyze the data using the QCA approach, a multi-step analysis was developed.

The results indicate five solutions that lead to high levels of customer satisfaction. The existence of multiple sufficient configurations for customer satisfaction indicates equifinality because multiple alternative solutions can lead to the same outcome.

The authors make a methodological contribution by applying the QCA method to the field of supply chain management and providing a detailed roadmap that supply chain researchers can utilize.

The authors provide managers five different and novel combinations of antecedents that lead to higher levels of customer satisfaction.

This study offers supply chain researchers a better understanding of when it is appropriate to use QCA and how to apply this methodology. From a theoretical perspective, past studies focused exclusively on the “net effects” of these antecedents, thus, did not capture the complexity of the relationships between these various antecedents and customer satisfaction. This is a noteworthy contribution as it highlights the complexity of the amalgam of relationships and factors that impact customer satisfaction within the context of reverse supply chain.