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This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.

This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.

A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.

A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.

The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.

This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.

This study aims to expose the challenges associated with theory development and its implementation, as it relates to services marketing and hospitality management. The author summarizes the literature, creates a conceptual model and proposes directions to bridge the theory–practice divide.

The author synthesizes and extends the literatures of services marketing, general marketing and hospitality management through a systematic literature review. A conceptual model is created to illustrate the challenges related to theory development and implementation.

Four types of theory challenges and three contemporary practical challenges are presented. The challenges for theory development include a communications gap, difficulties in applying universal theories into idiosyncratic organizations, researchers disconnected from practice and practitioners disconnected from research. Contemporary practical concerns include: human resource constraints, customer behavior and misbehavior and the organizational and business environment.

Managers can bring contemporary business challenges to the forefront by collaborating and writing with scholars. Similarly, keeping abreast of the latest advances in customer service, applying best practices in human resource management, educating and cocreating with customers are among several recommendations proposed to managers and marketers. Internal and external scanning can assure that managers engage in efforts to reduce barriers to implementation and improve services in their organizations.

Despite the decades-long study of customer service, organizations still struggle to deliver exceptional service. This study informs scholars on developing and communicating theories and managers on how to better access and interpret the latest research. In order for research to be successfully generated and implemented, scholars can engage in efforts aimed at joint (researchers and managers) idea generation, publication in multiple outlets, sampling that resembles real life, adoption of contingency theories and reconsidering journal editorial and institutional policies.

This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector. There are over 16,000 medical scientists (AIHW, 2019) in Australia responsible for carrying out pathology testing to help save the lives of thousands of patients every day. However, there are systemic shortages of medical scientists largely due to erratic rostering practices and workload issues. The purpose of this paper is to integrate evidence-based human resource management (EBHRM), the LAMP model and HR analytics to enhance line manager decision-making on rostering to support the wellbeing of medical scientists.

Using a qualitative methodological approach, the authors conducted 21 semi-structured interviews with managers/directors and nine focus groups with 53 medical scientists, making a total 74 participants from four large public hospitals in Australia.

Across four health services, manual systems of rostering and management decisions do not meet the requirements of the enterprise agreement (EA) and impact negatively on the wellbeing of medical scientists in pathology services. The authors found no evidence of the systematic approach of the organisations and line managers to implement the LAMP model to understand the root causes of rostering challenges and negative impact on employees. Moreover, there was no evidence of sophisticated use of HR analytics or EBHRM to support line managers' decision-making regarding mitigation of rostering related challenges such as absenteeism and employee turnover.

The authors contribute to HRM theory by integrating EBHRM, the LAMP model (Boudreau and Ramstad, 2007) and HR analytics to inform line management decision-making. The authors advance understandings of how EBHRM incorporating the LAMP model and HR analytics can provide a systematic and robust process for line managers to make informed decisions underpinned by data.

Research and experience show that evidence-based practice (EBP), i.e. using the best available knowledge in daily professional work, is difficult to achieve in social services. The purpose of this study is to understand the development of organizational EBP learning processes in daily work through workplace education for staff and managers of supported homes for people with cognitive disabilities. The authors examine how the EBP model and new knowledge are understood and made actionable in the workplace, applying theories of organizational learning.

The authors used empirical material collected from an EBP workplace education pilot in Sweden, as well as documents on national EBP implementation in Swedish social services. Before the pilot, a focus group interview was conducted with regional senior managers. Participating managers and staff were individually interviewed two to three years after the pilot.

The study illustrates how knowledge-based action emerged from education where EBP was interpreted, understood, reflected on, and tested, supported by codified EBP tools in the work context. The participants, when supervised, and when observing and questioning their own behaviors in practice, contributed to double-loop learning (DLL) processes. Codification of EBP knowledge into useful tools and socialization processes during education and workplace meetings was crucial in developing individual and group DLL and knowledge-based actions.

The bottom-up approach to EBP development and the adaptive contextual learning at the workplace gave new insights into organizational learning in social service workplaces.

The purpose of this paper is threefold. First, to explore the importance of specific work environment facets for the overall job satisfaction (JS) of primary full-time permanent teachers (PTs) and substitute/temporary teachers (STs). Second, to highlight the similarity or difference in JS patterns among PTs and STs. Third, to provide guidelines for effective evidence-based human resource management (HRM) interventions targeting to boost PTs and STs JS levels by considering: (1) the perceived importance of individual work facets for them and (2) the school's performance in providing a satisfactory work environment.

Data on overall and important JS facets (i.e. satisfaction with opportunities for self-fulfillment, work intensity/load, salary/income, leadership and collegial relations) were collected from a sample of 438 PTs and STs in Greece. Moreover, MUSA, a method that combines Multi-Criteria Decision (MCDA) and Importance-Performance Analysis (IPA), was applied to uncover the critical work environment facets of PTs and STs overall JS that call for interventions.

The findings suggest that PTs seem to value, more than STs, the transactional and economic aspects of the school environment. More precisely, on the part of PTs, self-fulfillment and salary/income are the main contributors to their JS, whilst leadership is the least important facet of JS. For STs self-fulfillment and collegial relationships are the aspects of work that contribute the most to their overall JS, whilst salary/income is the least important contributor. The study results further indicate that self-fulfillment is the strong attribute of Greek schools' work environment in boosting TJS regardless teachers' status, whilst salary/income and workload are potential threats.

It is one of the few studies that provide insights into the differing JS patterns of STs and PTs through the application of a MCDA/IPA method. Therefore, it offers evidence-based guidelines that take into consideration both the school's performance (overall and facet JS) and importance of core aspects of the work experience for STs and PTs.

The growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.

A portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.

The HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.

The framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.

The previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

As a result of COVID-19 and associated stay-at-home orders, the number of employees working remotely reached unprecedented levels during early periods of the pandemic. Since that time, some employees have returned to the office; yet, there is a lasting impact on employees’ desires for remote work. In response, decision-makers in organizations should be equipped with knowledge regarding what makes remote work beneficial for both employees and the organization and also fair and compliant with the law. This paper aims to take a dual perspective spanning human capital and legal aspects of remote work to offer six practical recommendations to organizations.

This paper reviews the human resources (HR) scholarly literature on remote work, using principles from evidence-based management to select valid and reliable findings in which to base practical recommendations for organizations. Associated legal risks are identified through a review of the legal literature on remote work and integrated into the recommendations.

Building on a multilevel model of HR practices, the authors offer the following six practical recommendations to organizations: offer hybrid work and both location and schedule flexibility; ensure fair and compliant work schedules; acknowledge manager perceptions; ensure fair approval and evaluation of remote workers; acknowledge individual workers; and align remote work practices with diversity, equity and inclusion efforts.

The multilevel model of remote work practices discussed in this paper offers an organizing framework for identifying advantages and disadvantages of remote work that future research may build upon. The six recommendations help bridge the research–practice gap by providing organizations with knowledge on how to maximize the benefits of remote work while mitigating potential legal risks.