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1 – 10 of over 1000Ransome Epie Bawack and Muhammad Ovais Ahmad
This paper seeks to examine how expectations from business analytics (BA) by members of agile information systems development (ISD) teams affect their perceptions and continuous…
Abstract
Purpose
This paper seeks to examine how expectations from business analytics (BA) by members of agile information systems development (ISD) teams affect their perceptions and continuous use of BA in ISD projects.
Design/methodology/approach
Data was collected from 153 respondents working in agile ISD projects and analysed using partial least squares structural equation modelling techniques (PLS-SEM).
Findings
Perceived usefulness and technological compatibility are the most salient factors that affect BA continuance intention in agile ISD projects. The proposed model explains 48.4% of the variance for BA continuance intention, 50.6% of the variance in satisfaction, 36.7% of the variance in perceived usefulness and 31.9% of the variance in technological compatibility.
Research limitations/implications
First, this study advances understanding of the factors that affect the continuous use of BA in agile ISD projects; second, it contextualizes the expectation-confirmation model by integrating technological compatibility in the context of agile ISD projects.
Originality/value
This is the first study to investigate BA continuance intention from an employee perspective in the context of agile ISD projects.
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Larissa Alves Sincorá, Marcos Paulo Valadares de Oliveira, Hélio Zanquetto-Filho and Marcelo Bronzo Ladeira
The survival and growth of organizations presently depend on managing processes and capabilities to effectively use large volumes of data from different sources to assist…
Abstract
Purpose
The survival and growth of organizations presently depend on managing processes and capabilities to effectively use large volumes of data from different sources to assist organizations’ strategic and operational goals. This paper aims to test the relationship between organizational analytical capabilities (OAC), the performance results in organizational resilience (OR) and the business process management maturity (BPMM).
Design/methodology/approach
Based on a survey of companies operating in the state of Espírito Santo, Brazil, a conceptual model was proposed and tested using the partial least squares algorithm.
Findings
The results confirm the proposed theoretical hypotheses that OAC and BPMM positively impact OR. In addition, the results show that OAC exert a moderating effect on the relationship between BPMM and OR.
Practical implications
It is understood that stimulating the practice of data and information analysis in the organizational routine translates into a relevant managerial behavior, as this attitude leverages the knowledge development and understanding about how to manage unexpected risk events, enabling companies to assess their ability to react to disruptions, even in terms of operational failures.
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Zohreh Pourzolfaghar, Marco Alfano and Markus Helfert
This paper aims to describe the results of applying ethical AI requirements to a healthcare use case. The purpose of this study is to investigate the effectiveness of using open…
Abstract
Purpose
This paper aims to describe the results of applying ethical AI requirements to a healthcare use case. The purpose of this study is to investigate the effectiveness of using open educational resources for Trustworthy AI to provide recommendations to an AI solution within the healthcare domain.
Design/methodology/approach
This study utilizes the Hackathon method as its research methodology. Hackathons are short events where participants share a common goal. The purpose of this to determine the efficacy of the educational resources provided to the students. To achieve this objective, eight teams of students and faculty members participated in the Hackathon. The teams made suggestions for healthcare use case based on the knowledge acquired from educational resources. A research team based at the university hosting the Hackathon devised the use case. The healthcare research team participated in the Hackathon by presenting the use case and subsequently analysing and evaluating the utility of the outcomes.
Findings
The Hackathon produced a framework of proposed recommendations for the introduced healthcare use case, in accordance with the EU's requirements for Trustworthy AI.
Research limitations/implications
The educational resources have been applied to one use-case.
Originality/value
This is the first time that open educational resources for Trustworthy AI have been utilized in higher education, making this a novel study. The university hosting the Hackathon has been the coordinator for the Trustworthy AI Hackathon (as partner to Trustworthy AI project).
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Vijay Pereira, Gopalakrishnan Narayanamurthy, Alessio Ishizaka and Noura Yassine
Vincent Patsy Katutsi, Will Kaberuka, Muhammed Ngoma, Bruno Lule Yawe, Ronnett Atukunda and Dickson Turyareba
This study aims to investigate the influence of specific socioeconomic factors, namely neighborhood, gender roles and affordability, on the continuous use of clean cooking…
Abstract
Purpose
This study aims to investigate the influence of specific socioeconomic factors, namely neighborhood, gender roles and affordability, on the continuous use of clean cooking technologies (CCTs) in households, using evidence from Uganda.
Design/methodology/approach
This study adopted an explanatory quantitative design. A questionnaire survey with 379 clean household responses was conducted. The data were analyzed using the Smart Partial Least Squares (PLS) software.
Findings
The results indicate that the sustained use of clean cooking technologies in households in Uganda is significantly associated with neighborhood influence, shared gender roles and affordability, collectively accounting for 27.7% of the variance.
Research limitations/implications
The three dimensions of socioeconomic factors under study partially explain the sustained use of CCTs in Uganda. The study does not delve into other socioeconomic factors that could probably account for 72.2% of the variance not explained. The quantitative design may have overlooked the social reality perspectives inherent in qualitative studies that other researchers may endeavor to exploit.
Originality/value
The authors integrated three dimensions of socioeconomic factors – neighborhood influence, gender roles and affordability – with the diffusion of innovation theory (DIT) using Smart PLS to explain the continuous use of CCTs within households.
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According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based…
Abstract
Purpose
According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.
Design/methodology/approach
This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.
Findings
The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.
Practical implications
This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.
Originality/value
This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.
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Jinou Xu and Margherita Emma Paola Pero
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…
Abstract
Purpose
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.
Design/methodology/approach
This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.
Findings
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.
Practical implications
A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.
Social implications
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.
Originality/value
This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.
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Orlando Troisi, Anna Visvizi and Mara Grimaldi
Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and…
Abstract
Purpose
Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.
Design/methodology/approach
The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.
Findings
The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.
Research limitations/implications
The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.
Originality/value
The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.
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Babajide Oyewo, Oluwafunmilayo Ajibola and Mohammed Ajape
This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate…
Abstract
Purpose
This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate (i.e. recency of adopting big data analytics (BDA) as a new idea) and usage level of BDA. Ten critical areas of BDA application to business and management consulting were investigated, (1) Human Resource Management; (2) Risk Management; (3) Financial Advisory Services; (4) Innovation and Strategy; (5) Brand Building and Product Positioning; (6) Market Research/Diagnostic Studies; (7) Scenario-Based Planning/Business Simulation; (8) Information Technology; (9) Internal Control/Internal Audit; and (10) Taxation and Tax Management.
Design/methodology/approach
Survey data was obtained through a structured questionnaire from one hundred and eighteen (118) consultants in Nigeria from diverse consulting firm settings in terms of size, international affiliation and scope of operation (Big 4/non-Big 4 firms). Data was analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance (MANOVA), multivariate discriminant analysis and multivariable logistic regression.
Findings
Whereas organizational characteristics such as firm size, international affiliation and scope of operation significantly determine the adoption rate of BDA, two attributes (international affiliation and scope of operation) significantly explain BDA usage level. Internationally affiliated consulting firms are more likely to record higher usage level of BDA than local firms. Also, the usage level of BDA by the Big 4 accounting/consulting firms is expected to be higher in comparison to non-Big 4 firms.
Practical implications
Contrary to common knowledge that firm size is positively associated with the adoption of an innovation, the study found no evidence to support this claim in respect of the diffusion of BDA. Overall, it appears that the scope of operation is the strongest organizational factor affecting the diffusion of BDA among consulting firms.
Originality/value
The study contributes to knowledge by exposing the factors promoting the uptake of BDA in a developing country. The originality of the current study stems from the consideration that it is the first, to the researchers' knowledge, to investigate the application of BDA by consulting firms in the Nigerian context. The study adds to literature on management accounting in the digital economy.
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B.S. Patil and M.R. Suji Raga Priya
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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