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Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

The purpose of this paper is to examine the contribution of big data in the transforming process of an IT firm to a learning organization.

The authors adopted a qualitative research approach to define and interpret the ideas and experiences of the IT firms’ employees and to present them to the readers directly. For this purpose, they followed a single-case study design. They researched on a small and medium enterprise operating in the IT sector in Düzce province, Turkey. This paper used a semi-structured interview and document analysis as data collecting methods. In all, eight interviews were conducted with employees. Brochures and website of the organization were used as data sources for the document analysis.

As a result of in-depth interviews and document analysis, the authors formed five main themes that describe perception of big data and learning organization concepts, methods and practices adopted in transforming process, usage areas of big data in organization and how the sample organization uses big data as a learning organization. The findings of this paper show that the sample organization is a learning IT firm that has used big data in transforming to learning organization and in maintaining the learning culture.

The findings contribute to literature as it is one of the first studies that examine the influence of big data on the transformation process of an IT firm to a learning organization. The findings reveal that IT firms benefit from the solutions of big data while learning. However, as the design of the research is single-case study, the findings may be specific to the sample organization. Future studies are required that examine the subject in different samples and by different research designs.

In literature, research on how IT firms’ managers and employees use big data in organizational learning process is limited. The authors expect that this paper will shed light on future research that examines the effect of big data on the learning process of the organization.

Cloud computing, a dominant technology, significantly impacts organizations, necessitating talent management strategies for sustained growth. This study aims to explore the impact of cloud adoption on large French organizations through a “learning organization” perspective.

Interviews were conducted with business and IT stakeholders from 35 multinational organizations in France.

Cloud services have a high impact on large organizations, leading to a demand for cloud-related skills, a power shift from IT to business departments and increased shadow IT activities. Effective utilization requires organizational learning and a change management project, transforming organizations into productive and innovative learning organizations.

This paper contributes to cloud computing, organizational learning and talent management literature, offering managers a novel approach to handling cloud services.

Business processing organizations are continuously focusing on customer knowledge management (CKM) due to the competitive business environment. CKM is being recognized as an essential source for improving organizational performance (OP). This study focuses on understanding CKM and its impact on OP. It also explores the moderating role of big data analytics capability (BDAC) on OP. Moreover, the mediating role of operational and strategic agility on OP was empirically tested.

Positivist research doctrine has been deployed and data was collected using structured survey using cross-sectional approach. The data were collected from 392 employees working in business processing software houses in the emerging market of Pakistan. Structural equation modeling (SEM) was deployed for the estimation of theoretical model.

The study's findings indicate that CKM has no significant impact on OP; although the presence of BDAC moderates the relationship significantly. Moreover, the study recommends that CKM and BDAC to be tested in the project environment, considering organization's operational and technical capabilities.

The study proclaims that BDAC can be helpful for organizations to improve their capabilities and output. Likewise, enhancing BDAC reduces failure rates of the projects.

This study provides a critical theoretical and practical contribution to project management in business processing organizations. Big data analytics can be of value for diagnostic, predictive and prescriptive analysis in the project management context.

Practitioners and academics are starting to recognize the benefits of green IT/IS practices. Despite these benefits, this study aims to know more regarding the factors that would drive organizations to use green IT/IS practices within their IT function and across the enterprise. To further understanding in this area, this study applies a strategic cognition framework of firm responsiveness and institutional theory to determine the extent to which an organization uses green IT/IS practices in response to stakeholder concerns. This study investigates the extent to which two organizational logics – expressive and instrumental – and three institutional pressures – coercive, mimetic and normative – jointly affect an organization's use of both green IT practices and green IS practices.

This study tested the hypotheses with survey data collected from 306 organizations. Structural equation modeling was used for data analysis.

Findings support four joint effects: (1) individualistic identity orientation and coercive pressure positively affect green IT practices; (2) collectivistic identity orientation and normative pressure positively influence green IS practices; (3) cost reduction orientation and mimetic pressure positively affect green IT practices; and (4) revenue expansion orientation and normative pressure positively influence green IS practices.

This study contributes to the literature by providing evidence for joint drivers of green IT and green IS practices. Green IT and IS practices represent organizations' different levels of commitment to environmental sustainability and responsiveness to stakeholders (i.e. green IT/IS practices). Organizations of different expressive and instrumental orientations are attuned to institutional pressures to various degrees, which leads to different green IT/IS practices.

The aim of this paper is to contribute to knowledge about the diversity of credibility arrangements in new audit spaces “in the margins” of auditing and the implications of such arrangements.

The paper is based on an in-depth qualitative study of the lesbian, gay, bisexual, transgender, queer and intersex (LGBTQI) rights certification run by the Swedish Federation for Lesbian, Gay, Bisexual, Transgender, Queer and Intersex Rights (RFSL) during its first decade of operation. We have interviewed employees and studied documents at the certification units within the RFSL. We have also interviewed certified organizations.

We highlight two features that explain the unusual credibility arrangements in this audit practice: the role of beneficiaries in the organizational arrangements chosen and the role of responsibility as an organizing value with consequences for responsibility allocation in this certification. These features make it possible for the RFSL to act as a credible auditor even though it deviates from common arrangements for credible audits.

The RFSL certification is different in several ways. First, the RFSL acts as both a trainer and an auditor. Second, the trainers/auditors at the RFSL have no accreditation to guarantee their credibility. Third, the RFSL decides for itself what standards should apply for the certification and adapts these standards to the operation being audited. Therefore, this case provides a good opportunity to study alternative credibility arrangements in the margins of auditing as well as their justifications.

The dynamics of work have increased the importance of work conditions and job demand in the corporate environment. This has exposed the high predominance of work overload among employees and managers in social organisations. This study aims to investigate the contemporary determinants of workaholism (organisational culture, financial well-being and career development) and quality of work-life (QWL) in Nigeria’s information technology (IT) sector.

To synthesise an understanding of factors that are responsible for workaholic behaviour among employees in the IT industry, this study used a cross-sectional research design to investigate the phenomenon that accounts for such hysteric conditions. This study administered an inventory battery of scales to obtain data from the study population on a random sampling technique to measure the established constructs responsible for workaholism and QWL. This study surveyed 644 samples of IT professionals in Nigeria and used structural equation modelling and artificial neural networks to examine the data obtained from the IT professionals.

The outcome of this study was significant as proposed. This study demonstrated that compulsive work approach adversely affects employee QWL in Nigeria’s IT industry. Also, excessive work adversely affects employee QWL in Nigeria’s IT industry. This study further discovered that organisational culture and management pressure significantly affect the QWL in the Nigerian IT industry. The results of this study showed that financial well-being significantly affects the QWL in the Nigerian IT industry. Lastly, it established that career development significantly affects the QWL in the Nigerian IT industry. This study concluded that if working round the clock is not completely removed from Nigeria’s IT cultural system, the industry will not be a safe environment and will not attract employees anymore. It has enabled many Nigerian workforces to quit working in Nigeria and migrate to international organisations.

This study has shown a meaningful dimension by discovering that workaholism is inherently in the cultural values and DNA of Nigerian IT institutions and not work addiction in itself for the employees. The novelty of this research has indicated that workaholism has not been documented much in the Nigerian IT sector.

Generic quality management system standard ISO 9001 and the automotive quality management system standard IATF 16949 both require organisations to demonstrate continual improvement in their customer satisfaction and the number of non-conformities identified during quality system audits. However, the long-term trends of these two parameters under ISO 9001 and IATF 16949 standards are not researched so far. It is expected that under continual improvement, organisations will achieve a step-function/stair-case shaped pattern. This study evaluates if this expectation is true when long-term performance of certified organisations is assessed.

A longitudinal exploration of three organisations certified to ISO 9001 standard and three certified to IATF 16949 standard is done. The observations are further substantiated using secondary data for the same ten years period about customer satisfaction of the major automobile manufacturers.

It is observed that none of the two indicators, i.e. the customer satisfaction and number of non-conformities, in any of the six organisations show step-wise/stair-case type improvement. All indicators followed random up and down patterns like ocean waves. It is paradoxical that certified organisations are claiming continual improvement and are remaining certified but there is actually no long-term improvement.

Longitudinal studies for the generic quality management standard ISO 9001 and the quality system standard for automotive sector IATF 16949 are rare. The revelation about ocean wave patterns observed in the long-term trends for customer satisfaction and the number of non-conformities in ISO 9001 and IATF 16949 certified organisations is a startling finding. It is outlandishly different from the conventional perception of a staircase-styled continual improvement pattern expected a priori in certified organisations.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

Information technology (IT) personnels’ technical, business and behavioral skills are critical enablers for generating IT value. In an increasingly digitalized working environment where non-IT employees participate in digital innovations, a focus on IT personnels’ skills only doesn’t meet researchers’ need for a framework to study digital skills and managers’ need to address digital skills challenges across an enterprise’s workforce. Nevertheless, the digital skills topic is complicated by conceptual ambiguity and a lack of theoretically derived and empirically validated model. The purpose of this study is to address this problem.

Theoretically, this study draws on human capital (HC) and resource-based view (RBV) theories. Empirically, it follows mixed method combining interviews and a survey.

The digital skills construct is a multidimensional second order reflective construct. While its development is influenced by an organization’s commitment and exposure to digitalization, it influences the value organizations obtain from digitalization.

This study conceptualizes the digital skills construct, identifying technology agnostic subdimensions that are meaningful beyond a particular digital domain [information and communication technology (ICT), information, Internet, Inter of Things (IoT)] and establishing a valid measure. Other researchers can improve both the indicators of the existing four conceptually distinct and managerially recognizable workplace digital skills dimensions as well as testing new ones.

Managers can use the instrument to assess the extent to which their non-IT workforces are equipped with digital skills and get strategic insights for specific interventions such as upskilling or buying in skills.

The main theoretical contribution of the paper is the conceptualization and validation of the digital skills construct for the non-IT workforce. Furthermore, we provide a theoretical framework to explain the factors that could influence the development of digital skills and demonstrate the impact that digital skills have on selected digitalization value indicators. This contribution provides the foundation for investigating the drivers, outcomes and the relationship of digital skills to other constructs such as digital transformation, innovation and firm performance.