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This paper aims to examine the influence of big data (BD) on human resource management (HRM). It defines how these data can be a useful tool in the decision-making process of companies’ human resources to obtain a sustainable competitive advantage.

This paper emphasizes the need to develop a holistic approach to emphasize these relations. Starting from these observations, the document proposes empirical research employing Eurostat data to test the benefits of BD in HRM decisions that optimize the relationship between training, productivity, and well-being.

The findings estimate HRM decisions and their impact in a broader macroeconomic and microeconomic perspective.

BD research is emerging as a crucial discipline in human resources. To overcome this problem, the paper develops an analysis of the literature on cleaner production and sustainability context; it creates a conceptual framework to clarify whether the existing studies consider the growing intensity of BD on human resources.

This study aims to scrutinize the relationship between the perception of big data (BD) features and the primary outcomes of financial accounting. Likewise, it explores whether financial accounting practices moderate the relationship between BD features and firm sustainability.

The study used a questionnaire survey based on the Likert scale for two distinct groups of participants: academic scholars and industry practitioners operating in the BD era within the energy sector.

The results reveal significant positive associations between BD features and firm performance, reporting quality, earnings determinants, fair value measurements, risk management, firm value, the efficiency of the decision-making process, narrative disclosure and firm sustainability. Besides, the path analysis indicates an indirect impact of BD on firm sustainability via financial accounting practices. The results suggest that energy firms should consider incorporating BD analysis into their financial accounting processes to improve their sustainability performance and create long-term value for their stakeholders.

The findings are particularly interesting to academics in accounting and business to improve the accounting curriculums to fit the technological revolution, especially in the field of BD analytics. Practitioners within energy industries must also refine their skills and knowledge to meet the challenges of BD in the foreseeable future. The results provide important implications for policy setters to revise current financial accounting standards to cope with technological innovation.

The study makes a valuable contribution by critically examining the impact of BD on various financial accounting practices neglected in prior research. It highlights the transformative power of BD in the domain of financial accounting and provides insights into its potential implications for energy firms.

Companies are turning to big data (BD) programs to help mitigate supply chain (SC) disruptions and risks that are increasing in frequency and severity. The purpose of this paper is to explore exactly how companies translate data into meaningful information used to manage SC risk and create economic value; an area not well researched. As companies are turning to big-data programs to help mitigate supply chain (SC) disruptions and risks that are increasing in frequency and severity, having the capability to internally integrate SC information is cited as the most critical risk to manage.

Information processing theory and resource-based view are applied to support capability development used to make value-based BD decisions. Semi-structured interviews were conducted with leaders in both the oil and gas industry and logistics SC partners to explore each companies’ BD transformation.

Findings illuminate how companies can build internal capability to more effectively manage SC risk, optimize operating assets and drive employee engagement.

The oil and gas industry were early adopters of gathering BD; more studies addressing how companies translate data to create value and manage SC risk would be beneficial.

Guidance for senior leaders to proactively introduce BD to their company through a practical framework. Further, this study provides insight into where the maximum benefit may reside, as data intersects with other company resources to build an internal capability.

This study presents a framework highlighting best practices for introducing BD plus creating a culture capable of using that data to reduce risk during design, implementation and ongoing operations. The steps for producing the maximum benefit are laid out in this study.

Big data analytics (BDA) plays a crucial role in understanding customer behavior through Customer Relationship Management (CRM), especially in a rapidly changing business environment. This paper investigates the direct effect of BDA use on market performance, besides the mediating effect through Big Data-enabled CRM strategies adoption (e.g. customization and personalization). The paper also examines the moderating role of competitive intensity in these effects.

Drawing from a knowledge-based view (KBV) and Organizational Information Processing Theory (OIPT), the authors formulated the research model. Subsequently, the measurement model and hypotheses were tested through PLS-SEM on online survey data of 229 managers from 167 companies out of Egypt's top 500.

The results indicated that BDA use does not directly affect the market performance, but this effect was significant through customization and personalization strategies adoption. The results also revealed a positive association between BDA use and the adoption of these strategies. Furthermore, competitive intensity only moderates the relationship between BDA use and personalization strategy adoption.

Companies can use BDA to improve customer knowledge and experience through customization and personalization, leading to better market performance and moving towards becoming a Big Data-driven organization. This study is limited to companies in the Egyptian context, which restricts the generalizability of the results.

This study conceptually and empirically explores how BDA usage, customization and personalization strategies impact market performance under competitive intensity situations, especially in the context of emerging markets.

This study aims to propose an integrated moderated mediation model to examine the process by which hotels obtain competitive advantage from the perspective of hotel managers.

After obtaining the agreement of the participants, a total of 560 candidates, all of whom were hotel managers, completed a survey administered online over a three-month period from November 2020 to January 2021. Ultimately, 257 valid responses were obtained after data screening by research assistants, for a response rate of 45.89%.

By reference to the concepts of big data (BD) and sustainability, the results show that BD management is a foundational attribute with respect to the indirect effects of BD analytics capabilities via proactive market orientation and social media collaboration. Furthermore, sustainability commitments and marketing are found to affect the relationship between such analytics capabilities and competitive advantage. Additionally, information sharing and food services have positive moderating effects that strengthen the changes in critical attributes during the process of obtaining competitive advantage.

To date, despite the proliferation of the concepts of BD, social media and sustainability, there is a lack of adequate empirical evidence and systematic literature reviews to comprehensively synthesize the emerging body of literature in the fields of tourism and hospitality research.

本研究于2020年11月到2021年1月的三个月期间, 在取得560位饭店管理者的同意后, 让他们完成了在线问卷调查。最终, 经过研究助理的数据筛选后, 收集到257份有效问卷, 有效回收率为45.89%。

本研究提出了一个调节式中介模型, 透过酒店管理者的角度来探讨酒店获得竞争优势的过程。

研究结果显示, 大数据管理透过参考大数据和永续的概念, 探讨主动式市场导向和社交媒体协作对大数据分析能力产生间接影响的基本重要归因。此外, 永续承诺和行销会影响分析能力与竞争优势之间的关系。再者, 信息共享和食品服务的关系起着显著的调节作用, 在获得竞争优势的过程中加强了关键属性间的关系。

迄今为止, 尽管大数据、社交媒体和永续的概念逐渐受到重视, 但仍缺乏足够的实证和系统性文献综整来阐逑观光餐旅研究文献缺憾。

Tras obtener el consentimiento de los participantes, un total de 560 candidatos, todos directores de hotel, completaron una encuesta online en un período de tres meses, desde noviembre de 2020 hasta enero de 2021. Finalmente, se obtuvieron 257 respuestas válidas tras un proceso de comprobación por los técnicos de investigación, lo que supone una tasa de respuesta del 45,89%.

Este estudio propone un modelo de mediación moderado integrado para examinar el proceso por el cual los hoteles obtienen ventajas competitivas desde la perspectiva de los directores de hotel.

Haciendo referencia a los conceptos de macrodatos y sostenibilidad, los resultados muestran que la gestión de macrodatos es un atributo fundamental para los efectos indirectos de las capacidades analíticas de macrodatos a través de la orientación proactiva al mercado y la colaboración en los medios sociales. Además, se observa que los compromisos de sostenibilidad y el marketing afectan a la relación entre dichas capacidades analíticas y la ventaja competitiva. Asimismo, el intercambio de información y los servicios de alimentación tienen efectos moderadores positivos que fortalecen los cambios en los atributos críticos durante el proceso de obtención de una ventaja competitiva.

Hasta la fecha, a pesar de la proliferación de los conceptos de macrodatos, medios sociales y sostenibilidad, se carece de evidencia empírica adecuada y de revisiones bibliográficas sistemáticas que sinteticen de forma exhaustiva la literatura emergente en los campos de investigación del turismo y la industria hotelera.

Despite that a transformational shift has occurred in many organisations towards data-driven management, many organisations struggle to harness and translate new technology, such as “big data” into a competitive advantage. This study aims to undertake an empirical investigation into the enabling factors which lead to the practice of formulating an effective data-led strategy (EDLS). Leveraging the theoretical lenses of the resource-based view, absorptive capacity and attention-focus view, a range of various factors are hypothesised to influence EDLS.

The study takes place in South Africa and is based on primary survey data focused on the Fin-tech industry sector where the need to formulate and implement an EDLS has become urgent considering the move to technology enabled banking solutions. Partial Least Squares Structural Equation Modelling (PLS-SEM) is used to test the hypotheses.

Results highlight that several factors are related to EDLS as significant predictors, which include the data platform, technical skills, knowledge management, transformation and focus-alignment. This latter factor has the largest influence on EDLS, which suggests that the alignment of focus across multiple firm divisions both vertically and horizontally significantly enables an EDLS.

Managers need to appreciate the intricacy of the range of factors involved in enabling an EDLS. Managers are advised to grow their organisational knowledge regarding which enablers offer the best pathway towards the development of a more robust framework when putting an EDLS into practice.

The article offers new insights into better understanding the relevant antecedents which enable the successful practice of an EDLS from an African emerging market perspective.

This paper aims to identify, synthesise and critically examine the extant academic research on the relation between big data analytics (BDA), corporate accountability and non-financial disclosure (NFD) across several disciplines.

This paper uses a structured literature review methodology and applies “insight-critique-transformative redefinition” framework to interpret the findings, develop critique and formulate future research directions.

This paper identifies and critically examines 12 research themes across four macro categories. The insights presented in this paper indicate that the nature of the relationship between BDA and accountability depends on whether an organisation considers BDA as a value creation instrument or as a revenue generation source. This paper discusses how NFD can effectively increase corporate accountability for ethical, social and environmental consequences of BDA.

This paper presents the results of a structured literature review exploring the state-of-the-art of academic research on the relation between BDA, NFD and corporate accountability. This paper uses a systematic approach, to provide an exhaustive analysis of the phenomenon with rigorous and reproducible research criteria. This paper also presents a series of actionable insights of how corporate accountability for the use of big data and algorithmic decision-making can be enhanced.

This paper discusses how NFD can reduce negative social and environmental impact stemming from the corporate use of BDA.

To the best of the authors’ knowledge, this paper is the first one to provide a comprehensive synthesis of academic literature, identify research gaps and outline a prospective research agenda on the implications of big data technologies for NFD and corporate accountability along social, environmental and ethical dimensions.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

The research aims at finding out the extent to which such urban transformation projects—in terms of their design components and aspects—contribute to providing big data (BD) with effective datasets, which are considered a key requirement in operating smart city solutions.

The present research investigates the predisposition level of these projects for supporting the BD through one of the urban initiatives for humanizing neighborhoods in Al Riyadh city (KSA). The selected case is analyzed by mapping the functional performance of its design features with certain characteristics of BD.

One of the core conclusions is: Despite the readiness of the design components of these projects to provide high levels of integration with IoT and smart transformation, the level of application is lower than expected on account of the dearth of initial targets and strategies, especially the lack of a supporting environment, street facilities and security and safety datasets.

The answer—arrived at through both descriptive and analytical approaches—is expected to guide those who query the further key concept of smart applications—is the answer characterized as technologically based, or is the same based on human aspects?

In the contemporary period, numerous businesses undergo significant adjustments, such as evaluating critical components of the corporate operations and relying on technology to keep operations running while conforming to an ever-changing set of norms and new tactics. The present study aims to (1) explore the relationship between Industry 4.0 (I4.0) tools and their impact on organizational performance and (2) find evidence supporting the moderating role of remote working and organizational agility (OA) in enhancing organizational performance.

The study employed the quantitative research method, and the data were collected from individuals working in different Asian IT firms using the previously established questionnaire. The data were examined using SPSS v22. Different statistical tests have been performed to find the relationship among constructs.

This study uncovers that I4.0 tools impact organizational performance, especially in the IT sector, with a particular emphasis on the moderating influence of remote work and OA. I4.0 tools encompass pivotal components such as artificial intelligence (AI), big data (BD), cloud computing (CC) and Internet of Things (IoT) indeed augment organizational performance. It can be referenced that I4.0 tools play the role of a driving force that equips organizations with the knowledge to augment their performance.

Companies should encourage remote work and use I4.0 technology to support and manage it. Enabling people to work from any location, lowering the requirement for physical infrastructure and enabling a more flexible and responsive organizational structure can increase OA. In conclusion, firms in Asia may increase the performance and agility using I4.0 technology. Organizations may innovate by putting money into these technologies, encouraging remote work and creating an innovative culture.

In this dynamic and technologically advanced environment, every industry is forced to look for latest tools, i.e. I4.0, tools to augment the performance. It has been concluded that I4.0 tools are “better practices” for boosting organizational performance; hence, the findings benefit firms working in the IT sector. The verdicts of this research can assist organizations in making decisions regarding the implementation of I4.0 tools.

To the best of the authors' knowledge, no specific study could be found in which the relationship among these constructs had been investigated earlier in the IT sector. This research work acts as value addition to the literature as it illustrates technological advancements may increase organizational performance, especially in Asia. This research work adds to the body of knowledge by amplifying the effect of latest technologies on organizational performance, via remote work and OA.