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This paper aims to explore the role of human resource (HR) analytics on employees’ willingness to improve performance. In doing so, the paper examines issues related to the performance appraisal (PA) system which affect employees’ willingness to improve performance and how HR analytics can be a potential solution to deal with such issues.

The paper develops a conceptual framework along with propositions by integrating both academic and practitioner literatures, in the field of HR analytics and performance management.

The paper proposes that the use of HR analytics will be negatively related to subjectivity bias in the PA system, thereby positively affecting employees’ perceived accuracy and fairness. This further positively affects employees’ satisfaction with the PA system, which subsequently increases employees’ willingness to improve performance.

The paper provides implications for both researchers and practitioners in the performance management area for improving employees’ performance by applying HR analytics as a strategic tool in the PA system. It also provides implications for future researchers to empirically test the conceptual framework in different organizational settings.

The paper offers insights into how the use of HR analytics can deal with issues of subjectivity bias in the PA system and positively affects employees’ willingness to improve performance.

Big data analytics (BDA) helps service providers with customer insights and competitive information. It also empowers customers with insights about the relative merits of competing services. The purpose of this paper is to address the research question, “How does big data analytics enable frontline employees (FLEs) in effective service delivery?”

The research develops schemas to visualise service contexts that potentially benefit from BDA, based on the literature drawn from BDA and FLEs streams.

The business drivers for BDA and its level of maturity vary across firms. The primary thrust for BDA is to gain customer insights, resource optimisation and efficient operations. Innovative FLEs operating in knowledge intensive and customisable settings may realise greater value co-creation.

There exists a considerable knowledge gap in enabling the FLEs with BDA tools. Managers need to train, orient and empower FLEs to collaborate and create value with customer interactions. Service-dominant logic posits that skill asymmetry is the reason for service. So, providers need to enhance skill levels of FLEs continually. Providers also need to focus on market sensing and customer linking abilities of FLEs.

Both firms and customers need to be aware of privacy and ethical concerns associated with BDA.

Knitting the BDA and FLEs research streams, the paper analyses the impact of BDA on service. The research by developing service typology portrays its interplay with the typologies of FLEs and BDA. The framework portrays the service contexts in which BD has major impact. Looking further into the future, the discussion raises prominent questions for the discipline.

Rational use of the information available to companies is one of the strategic concerns for both family businesses and non-family businesses. The aim is to make the best use of the information resulting from data analysis in order to gain strategic advantage and to be more competitive as a company in all its functional areas. Experience indicates that emotions play an important role, especially in family businesses. Many maturation models exist to analyze decision-making processes (DMPs), but none from the perspective of family business cognition. The authors start from their own “Circumplex Hierarchical Representation of Organisation Maturity Assessment” (CHROMA) model (Parra, Tort-Martorell, Ruiz-Viñals, & Alvarez-Gomez, 2017), which was created to support decision processes in family businesses. This model was proven successful in the analysis of DMPs in large family businesses. The model was simplified as CHROMA-SHADE (Parra, Tort-Martorell, Ruiz-Viñals, & Alvarez-Gomez, 2019), more adequate for the analysis of small and medium-sized family businesses. Despite being a good DMP analysis instrument, intangible aspects such as family values and emotions have not yet been included. Both entrepreneurial emotions and entrepreneurial cognition must be taken into account when analyzing the DMP of the family business. In this chapter, the authors wish to explore attributes that can be introduced into a new dimension in the CHROMA model in order to make it more specific in the analysis of DMPs of family businesses regardless of size. The resulting FAMILY-CHROMA model represents a specific maturation model to evaluate DMPs based on the use of business information of family businesses.

The purpose of this paper is to develop a framework and propositions to advance research and practice in sustainable supply chain management (SSCM). Performance indicators (economic, environmental, and social) identified in the paper aim to facilitate empirical testing of a range of theoretical models derived or extended from the stated propositions.

The study of SSCM is truly complicated, and there is no one theory that applies in all instances. The authors analyzed over 200 critical articles published in major supply chain management and sustainability-based journals and grounded the proposed framework in a multi-theoretical perspective.

SSCM implementation entails linking stakeholder pressures, moral motives, and management commitment with relational practices. The paper further elucidates how relational practices, when bundled together, can create a set of relational capabilities, which in turn transform stakeholder pressures into sustainable outcomes.

The research framework contributes to SSCM theory building insofar as it can be expanded into various theoretical models, allowing researchers to empirically test the links among SSCM drivers, management commitment, and relational capabilities, along with their individual or collective impact on supply chain performance.

The framework provides a roadmap for firms to develop and nurture relational capabilities while dealing with growing stakeholder pressures. Moral motives strengthen top management commitment, which helps channel stakeholder pressures toward the proactive development of relational capabilities.

The paper fulfills a call for utilizing multiple theoretical lenses to examine complex SSCM phenomena and, ultimately, to create a coherent theory of SSCM.

Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA.

Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies.

Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment.

Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities.

This study provides useful management insights into the effective use of BA for improving organizational performance.

The nature of technologies that are recognised as Artificial Intelligence (AI) has continually changed over time to be something more advanced than other technologies. Despite the fluidity of understanding of AI, the most common theme that has stuck with AI is ‘human-like decision making’. Advancements in processing power, coupled with big data technologies, gave rise to highly accurate prediction algorithms. Analytical techniques which use multi-layered neural networks such as machine learning and deep learning have emerged as the drivers of these AI-based applications. Due to easy access and growing information workforce, these algorithms are extensively used in a plethora of industries ranging from healthcare, transportation, finance, legal systems, to even military. AI-tools have the potential to transform industries and societies through automation. Conversely, the undesirable or negative consequences of AI-tools have harmed their respective organisations in social, financial and legal spheres. As the use of these algorithms propagates in the industry, the AI-based decisions have the potential to affect large portions of the population, sometimes involving vulnerable groups in society. This chapter presents an overview of AI’s use in organisations by discussing the following: first, it discusses the core components of AI. Second, the chapter discusses common goals organisations can achieve with AI. Third, it examines different types of AI. Fourth, it discusses unintended consequences that may take place in organisations due to the use of AI. Fifth, it discusses vulnerabilities that may arise from AI systems. Lastly, this chapter offers some recommendations for industries to consider regarding the development and implementation of AI systems.

This chapter explores the evolution of a network, initially based on providing sustainable seafood through Loblaw’s supply chain, to a network that is collectively working to improve ocean health. It describes the role of the CEO and key managers, the internal changes taken by Loblaw to become a more sustainable organization, and the external partnering that resulted in a more coherent network with shared goals.

The chapter describes models and theories of sustainable organizations, issue nets, and collaboration and then applies the concepts to understand Loblaw’s sustainability journey and the creation of a network.

The model of the evolution to a sustainable organization is extended to include the journey to sustainable issue or domain networks. What Loblaw and the partnering organizations were able to create suggests that there are increasing levels of collaboration around changing a domain, if there is the courage to take a leap of faith and increase an organization’s time horizon beyond immediate financial demands.

The findings of this chapter will help senior executives with responsibility for shifting supply chains to become more sustainable. In addition, this case provides a new level of detail in describing the journey to sustainability, shifting from a company focus to an issue focus.

This chapter discusses the evolvement of the sustainability concept and its importance in the strategic management context. First, the authors review the development of the concept over the last century and presents the most commonly used sustainability definitions. Then, the three pillars of sustainability (economic, natural and social) are reviewed, highlighting the sustainability aspect of each pillar individually and the problems of their non-substitutability, irreversibility and non-linearity. Based on the literature review, this chapter discusses the main motives for integration of sustainability concept into the overall strategy of the company, namely compliance with regulation, response to public concern, expected competitive advantage and top management commitment. Furthermore, important distinctions between reactive and proactive approaches are presented, and the results and benefits (such as cost reductions, differentiation and added value) of proactive approaches to corporate sustainability are analyzed. Nevertheless, such benefits can only be achieved if corporate sustainability is understood and treated as a holistic concept, which is deeply embedded in the company’s strategy and is approached proactively from the interdisciplinary viewpoint, looking at all three dimensions simultaneously.

Higher education can offer hope and a way forward for vulnerable populations. In particular, access to internationally recognized degrees and credentials has the potential to be a key protection priority for refugee populations, opening alternative solutions to displacement through economic empowerment and increased mobility.

While innovations in online learning have opened new pathways, the delivery of higher education to refugee learners in resource-deprived settings – including camps and urban environments – remains notoriously challenging. Therefore, there is an imperative to draw upon lessons learned from existing programs in order to identify promising practices and emerging innovations.

In this chapter, we draw on our experiences of developing a higher education model for refugee and vulnerable learners to argue that successful delivery of accredited degrees to populations affected by forced displacement relies upon the following three key elements:

• 1)

  Flexible mode of degree delivery and assessment.

• 2)

  Robust blended learning model with in-person academic support.

• 3)

  Provision of adaptive and context-specific interventions and resources.

Flexible mode of degree delivery and assessment.

Robust blended learning model with in-person academic support.

Provision of adaptive and context-specific interventions and resources.

The case study for this chapter is an initiative called the Global Education Movement at Southern New Hampshire University, which delivers accredited degrees to refugee and refugee-hosting populations in five countries. Evidence from the program in Rwanda, operated in partnership with a local partner, Kepler, suggests it is possible for a full degree program to be successful in reaching vulnerable learners, including refugees.