Understanding the adoption and institutionalization of workforce analytics: A systematic literature review and research agenda

Data analytics plays a crucial role in enhancing organizational decision-making. Various organizational disciplines have already embraced data analytics. However, human resources management is lagging in data-driven decision-making and, specifically, workforce analytics. Although an increasing number of studies explore the diffusion of workforce analytics, our understanding of why organizations decide to adopt workforce analytics and how organizations further institutionalize workforce analytics remains limited. Taking an HRM innovation and contextualized perspective, this systematic literature review aims to provide in-depth knowledge on factors driving workforce analytics adoption and institutionalization. The results, including relevant learnings from business analytics research, show the importance of competitive, institutional, heritage mechanisms, key decision-makers and actors, and HRM fit-related factors in the diffusion process. Based on the results of this review, various avenues for future research are presented. Additionally, insights from this literature review can help decision-makers allocate their scarce resources effectively and efficiently to cultivate workforce analytics as an organizational practice.     

Enabling supply chain analytics for enterprise information systems: a topic modelling literature review and future research agenda

ABSTRACT

This paper provides a literature review of the research within the framework of 1) analytics,2) supply chain management, and 3) enterprise information systems, and relate the findings to competitive enablers. The findings are used to construct a future research agenda. The methodology is a systematic two-stage approach, based on a Smart Literature review framework using topic modelling. The research agenda proposes future research within the themes of 1) context, 2) cross-functional analytics, 3) cross-planning level analytics, 4) implementation and assimilation of analytics in EIS, 5) analytics and big data for SCM, 6) managerial aspects of analytics, and 7) data and system heterogeneity.     

Internet-of-things enabled supply chain planning and coordination with big data services: Certain theoretic implications

Recent advances in information technology have led to profound changes in global manufacturing. This study focuses on the theoretical and practical challenges and opportunities arising from the Internet of Things (IoT) as it enables new ways of supply-chain operations partially based on big-data analytics and changes in the nature of industries. We intend to reveal the acting principle of the IoT and its implications for big-data analytics on the supply chain operational performance, particularly with regard to dynamics of operational coordination and optimization for supply chains by leveraging big data obtained from smart connected products (SCPs), and the governance mechanism of big-data sharing. Building on literature closely related to our focal topic, we analyze and deduce the substantial influence of disruptive technologies and emerging business models including the IoT, big data analytics and SCPs on many aspects of supply chains, such as consumers value judgment, products development, resources allocation, operations optimization, revenue management and network governance. Furthermore, we propose several research directions and corresponding research schemes in the new situations. This study aims to promote future researches in the field of big data-driven supply chain management with the IoT, help firms improve data-driven operational decisions, and provide government a reference to advance and regulate the development of the IoT and big data industry.     

Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics

The increasing use of People Analytics to manage people in organizations ushers in an era of algorithmic management. People analytics are said to allow decision-makers to make evidence-based, bias-free, and objective decisions, and expand workers' opportunities for personal and professional growth. Drawing on a virtue ethics approach, we argue that the use of people analytics in organizations can create a vicious cycle of ethical challenges - algorithmic opacity, datafication, and nudging - which limit people's ability to cultivate their virtue and flourish. We propose that organizations can mitigate these challenges and help workers develop their virtue by reframing people analytics as a fallible companion technology, introducing new organizational roles and practices, and adopting alternative technology design principles. We discuss the implications of this approach for organizations and for the design of people analytics, and propose directions for future research.     

Big data analytics and enterprises: a bibliometric synthesis of the literature

ABSTRACT

Understanding the developmental trajectories of big data analytics in the corporate context is highly relevant for information systems research and practice. This study presents a comprehensive bibliometric analysis of applications of big data analytics in enterprises. The sample for this study contained a total of 1727 articles from the Scopus database. The sample was analyzed with techniques such as bibliographic coupling, citation analysis, co-word analysis, and co-authorship analysis. Findings from the co-citation analysis identified four major thematic areas in the extant literature. The evolution of these thematic areas was documented with dynamic co-citation analysis.     

Are firms ready to use big data analytics to create value? The role of structural and psychological readiness

In this study, we leverage Information Technology (IT) readiness literature and resource-based view (RBV) to investigate the impact of firm structural and psychological readiness on firm value creation, as mediated by big data analytics usage. The proposed research model is empirically validated using survey data from 179 senior IT managers. The findings demonstrate the importance of both structural (i.e. IT infrastructure capability, tools functionality, employee analytical capability, and bigness of data) and psychological readiness (i.e. IT proactive climate) in enhancing firm value creation through big data analytics usage. These results provide interesting theoretical and practical insights.     

A Survey of Differentially Private Regression for Clinical and Epidemiological Research

Differential privacy is a framework for data analysis that provides rigorous privacy protections for database participants. It has increasingly been accepted as the gold standard for privacy in the analytics industry, yet there are few techniques suitable for statistical inference in the health sciences. This is notably the case for regression, one of the most widely used modelling tools in clinical and epidemiological studies. This paper provides an overview of differential privacy and surveys the literature on differentially private regression, highlighting the techniques that hold the most relevance for statistical inference as practiced in clinical and epidemiological research. Research gaps and opportunities for further inquiry are identified.     

Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?

Simple, transparent rules are often frowned upon while complex, black-box models are seen as holding greater promise. Yet in quickly changing situations, simple rules can protect against overfitting and adapt quickly. We show that the surprisingly simple recency heuristic forecasts more accurately than Google Flu Trends (GFT) which used big data analytics and a black-box algorithm. This heuristic predicts that “this week’s proportion of flu-related doctor visits equals the proportion from the most recent week.” It is based on psychological theory of how people deal with rapidly changing situations. Other theory-inspired heuristics have outperformed big data models in predicting outcomes, such as U.S. presidential elections, or other uncertain events, such as consumer purchases, patient hospitalizations, and terrorist attacks. Heuristics are transparent, clearly communicating the underlying rationale for their predictions. We advocate taking into account psychological principles that have evolved over millennia and using these as a benchmark when testing big data models.     

HR and analytics: why HR is set to fail the big data challenge

The HR world is abuzz with talk of big data and the transformative potential of HR analytics. This article takes issue with optimistic accounts, which hail HR analytics as a ‘must have’ capability that will ensure HR's future as a strategic management function while transforming organisational performance for the better. It argues that unless the HR profession wises up to both the potential and drawbacks of this emerging field and engages operationally and strategically to develop better methods and approaches, it is unlikely that existing practices of HR analytics will deliver transformational change. Indeed, it is possible that current trends will seal the exclusion of HR from strategic, board‐level influence while doing little to benefit organisations and actively damaging the interests of employees.     

Organizational change techniques: their present, their future

To help carry out their responsibility of managing rapid and often unexpected change, managers have an available set of techniques: organizational behavior modification, management by objectives, management development, organization development, management auditing, and a control cycle of planning, implementation, and control. Each of these has a format that species the procedures to be followed to bring about organizational change. Michael emphasizes that such formats are preferable to a haphazard, trial-and-error approach that may produce unanticipated results. In part because some techniques are newer than others, data from a research project of planning and control that Michael conducted show different rates of usage by a sample of Fortune 500 companies. The control cycle is the most widely used; organizational behavior modification the least widely used. The use of these techniques of organizational change is likely to vary in some ways and experience may bring about changes in the techniques. Michael concludes that the newer breed of managers who are versed in the social sciences, mathematics, and the computer are likely to spread new techniques in the organizational world.     

Revisiting IS research practice in the era of big data

Through building and testing theory, the practice of research animates data for human sense-making about the world. The IS field began in an era when research data was scarce; in today's age of big data, it is now abundant. Yet, IS researchers often enact methodological assumptions developed in a time of data scarcity, and many remain uncertain how to systematically take advantage of new opportunities afforded by big data. How should we adapt our research norms, traditions, and practices to reflect newfound data abundance? How can we leverage the availability of big data to generate cumulative and generalizable knowledge claims that are robust to threats to validity? To date, IS academics have largely welcomed the arrival of big data as an overwhelmingly positive development. A common refrain in the discipline is: more data is great, IS researchers know all about data, and we are a well-positioned discipline to leverage big data in research and teaching. In our opinion, many benefits of big data will be realized only with a thoughtful understanding of the implications of big data availability and, increasingly, a deliberate shift in IS research practices. We advocate for a need to re-visit and extend traditional models that are commonly used to guide much of IS research. Based on our analysis, we propose a research approach that incorporates consideration of big data—and associated implications such as data abundance—into a classic approach to building and testing theory. We close our commentary by discussing the implications of this hybrid approach for the organization, execution, and evaluation of theory-informed research. Our recommendations on how to update one approach to IS research practice may have relevance to all theory-informed researchers who seek to leverage big data.     

Creating accountability through HR analytics – An audit society perspective

This paper introduces an accountability-based perspective of the effects of implementing HR analytics. Considering central arguments about HR analytics' potential to transform HRM and using research on the audit society and concepts from critical accounting research, we develop a framework that analyzes the emergence of three forms of accountability in HRM: accountability through exposure, design, and connectivity. The paper contributes to research on HR analytics by identifying three forms of accountability in HRM that result from implementing HR analytics and by determining how they influence how HRM is understood, how HR practices are augmented, and how HRM's status in organizations can be improved.     

Shocks and final straws: Using exit‐interview data to examine the unfolding model's decision paths

The unfolding model emphasizes the role of shocks (jarring events that initiate exit cognitions) in the turnover process. In contrast to earlier survey‐based research, we used exit interviews to classify organizational leavers along the model's paths. The data provide support for the model but highlight several aspects of shocks not addressed by previous research. Employees on the same path may experience distinctly different shock subgroups (e.g., work or nonwork), some employees require shock combinations (e.g., push and pull shocks) to motivate leaving, and some dissatisfied employees experience shock‐like events (final straws) that confirm previous exit cognitions rather than initiate them. The research demonstrates how organizations can use exit interviews to better understand their employee exit patterns. © 2012 Wiley Periodicals, Inc.     

Employee lactation: A review and recommendations for research,practice, and policy

Recent social justice movements call for an increased focus on workplace diversity, equity, and inclusion. Given the large proportion of working mothers who return to work after having a baby, research about lactation, work, and human resources issues is sorely needed to increase knowledge and understanding of working and lactating mothers' needs so that they feel welcome, respected, and supported in the workplace. For mothers who feed their baby breastmilk, concurrently managing work responsibilities and lactation demands can be a substantial source of employee stress and can create work-family conflict. Research on workplace lactation across a variety of disciplines has increased over the past decade. As attention to lactation is slowly increasing in the management and organizational behavior literature, synthesizing research from other domains into the organizational and managerial sciences is a critical precursor to facilitating future research in the field as well as translating that research into meaningful action in organizations. We contribute to filling this gap, by reviewing and coalescing research across relevant domains, grounding it in extant theory, and offering a conceptual model suggesting the critical antecedents that facilitate employee lactation behaviors, and the work-related moderators that meaningfully impact those relationships. Finally, we offer recommendations to guide future research both methodologically and substantively so as to advance management theory and research surrounding employee lactation at work, and offer practical implications for organizations as well as for public policy.     

Systems for Sustainable Organizations: Emergent Strategies,Interactive Controls and Semi-formal Information

New-form organizations are likely to organize more explicitly around processes than traditional-form organizations that emphasize functional hierarchy. Developing process-based strategic responses quickly using diffuse sets of resources is likely to play an increasingly important role in sustaining new organizational forms. Three ideas introduce alternative perspectives on strategy formulation, management control and information systems design that may be useful in understanding organizational performance in this area. They focus on: (1) emergent strategies, (2) interactive management controls, and (3) semi-formal systems. In combination these three perspectives describe relationships between strategy, organizational design and systems support that suggest mechanisms for improving the sustainability of new organizational forms. To some degree distributed organizational structures such as networked organizations and quasi-organizational forms such as alliances, partnerships and joint ventures represent attempts to solve a paradox of competitive agility. This paradox suggests that in the context of rapidly changing, increasingly global markets, organizations need to be flexible (so they can respond quickly to competitive threats) yet remain stable (so they can learn and grow based on their strengths). If this is the case, what systems and tools are available that encourage a productive balance between flexibility and stability? This paper uses the experience of regional management teams at a large consumer goods company to suggest how interactive controls and semi-formal information systems combine to increase the agility of a distributed organization that can employ emergent strategies. Evidence illustrates some of the mechanisms by which (a) faster response times deliver organizational flexibility while (b) semi-formal analytics add the stability of knowledge and guidance shared across organizational sites. Examples discuss the use of information within management teams, discussion behaviour within management meetings, and organizational performance in response to crisis events. In this context the paper analyses the characteristics of new-form systems that could be used to sustain new-form organizations While the development of process-oriented semi-formal systems is just beginning, the potential for linking such technology with newly developed approaches to management control appears to have important implications for the practice and performance of management in new-form organizations. In particular, interactive controls and semi-formal information appear to offer leverage as mechanisms for organizational adjustment during times when organizations must exploit emergent strategies     

Human resource metrics and decision support: A classification framework

Human resource information systems and analytics have transformed the delivery of HR services and the role of HR within organizations. In spite of the complexity of HR and the different roles HR plays, there has been limited research which helps inform the selection, application and use of HR metrics and analytics to the operational, managerial, and strategic levels that HR occupies. Therefore, the goal of this article is to provide a framework that describes the data needs, decision characteristics, and HR metrics to these different levels of HR activity and decision-making. We provide a number of research propositions and implications of the model. We finish the paper with a discussion of the implications that this framework has for how HR decisions are made, the types of data used in support of these decisions, and the metrics used.     

Pay Dispersion and Organizational Performance in Korea: Curvilinearity and the Moderating Role of Congruence with Organizational Culture

This study examines the curvilinear relationship between pay dispersion and organizational performance. According to the pay dispersion literature, a large pay gap has benefits and drawbacks for organizational performance because employees can feel motivated or demotivated depending on the degree of pay dispersion. We investigate the possibility of nonlinearity in the context of these countervailing forces, and aim to uncover the condition under which the positive effect of high pay dispersion prevails. Our empirical analysis of data from 436 Korean cross-industry firms shows that pay dispersion and organizational performance have an inverted U-shaped relationship. Moreover, when a pay scheme matches current organizational culture, the positive relationship between pay dispersion and organizational performance is more pronounced. We discuss the implications for future compensation research and practice.