Unilever uses management development (MD) as a strategic tool to help the organization meet its short and long term goals. In recent years, Unilever has undergone a process of…
Abstract
Unilever uses management development (MD) as a strategic tool to help the organization meet its short and long term goals. In recent years, Unilever has undergone a process of rapid change and MD has been important in communicating that change throughout the organization and equipping staff to deal with it. Key features that have made the MD programme work in this way for Unilever were: joint ownership and responsibility (the business and the individual); identification of talent at all levels; explicit incorporation of own wishes; company interests can take precedence over group interests; one system worldwide; performance‐development related pay; and total transparency. In addition, performance development planning is highlighted as a major component of the programme.
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While the name Unilever is familiar to most people, its size takes some grasping. There are 300 operating units in 88 countries and more than 1,000 strong successful brands, which…
Abstract
While the name Unilever is familiar to most people, its size takes some grasping. There are 300 operating units in 88 countries and more than 1,000 strong successful brands, which are marketed in more than 150 countries. Its pre‐packaged branded foods are household names, though many will be unaware that the likes of Magnum ice cream, Lipton tea and Omo detergent are Unilever products. The operating profit for 1999 was $4.6bn. Two parent companies operate almost entirely independently in Holland and the UK while, to serve consumers competitively, brands are tailored for different regions and countries.
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Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of…
Abstract
Purpose
Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.
Design/methodology/approach
A structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.
Findings
This literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.
Originality/value
This paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.
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Hamid Reza Saeidnia, Elaheh Hosseini, Shadi Abdoli and Marcel Ausloos
The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the…
Abstract
Purpose
The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.
Design/methodology/approach
By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.
Findings
(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.
Originality/value
This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.
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Ewout Reitsma, Peter Manfredsson, Per Hilletofth and Roy Andersson
The aim of this study is to investigate the outcomes of a leading Swedish truck maker (referred to as “TruckCo” for confidentiality reasons) providing lean training to its…
Abstract
Purpose
The aim of this study is to investigate the outcomes of a leading Swedish truck maker (referred to as “TruckCo” for confidentiality reasons) providing lean training to its strategic suppliers.
Design/methodology/approach
A single in-depth case study is conducted, using on-site semi-structured interviews with representatives from TruckCo and its suppliers for data collection.
Findings
The lean training program resulted in four main outcomes. First, financially unstable suppliers were less receptive to the lean training program than financially stable suppliers. Second, the suppliers became easier to collaborate with over time, through improving their internal ways of working and thus creating more trust in terms of reliability. Third, the suppliers improved their ability to identify possible problems that could jeopardize deliveries. Fourth and finally, the suppliers improved their delivery precision.
Research limitations/implications
One limitation of this study is that its findings are based on a single in-depth case study. Another limitation is that all the involved companies originate from Sweden. These limitations should be considered in attempts to replicate or further test the reported findings.
Practical implications
This study provides insights into how a manufacturer can teach lean management to suppliers, and how suppliers can be involved in a manufacturer's journey towards a leaner supply chain. Furthermore, the study reflects more generally on the potential outcomes of a manufacturer providing lean training to suppliers.
Originality/value
This study highlights both TruckCo's and the suppliers' view of the outcomes of the lean training program and discusses how different suppliers adopt the taught lean practices. Avenues for future research are proposed as well.
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Mariana Velykodna, Oksana Tkachenko, Oksana Shylo, Kateryna Mitchenko, Zoia Miroshnyk, Natalia Kvitka and Olha Charyieva
This study aims to develop and test a multivariable psychosocial prediction model of subjective well-being in Ukrainian adults (n = 1,248) 1.5 years after the 2022 Russian…
Abstract
Purpose
This study aims to develop and test a multivariable psychosocial prediction model of subjective well-being in Ukrainian adults (n = 1,248) 1.5 years after the 2022 Russian invasion of Ukraine.
Design/methodology/approach
The research design followed the “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The online survey combined a questionnaire on sociodemographic characteristics and specifics of living in wartime, as well as validated self-reported inventories: The Modified BBC Subjective Well-being Scale, Acceptance and Action Questionnaire – Version 2 and Connor–Davidson Resilience Scale-10.
Findings
The initially developed model was tested through regression analysis, which revealed nine variables as predictors of the subjective well-being scores within the sample, explaining 49.3% of its variance. Among them, the strongest were living with a friend and receiving mental health care systematically. They were almost twice as influential as forced displacement abroad and trauma exposure, which predicted lower well-being, and living with a spouse, which forecasted higher well-being scores. Two resilience subscales – adjustment and restoring and resistance – as predictors of better well-being and perceived unsuccess in life and age as predictors of lower well-being were relatively weaker but statistically significant.
Originality/value
The obtained results support the previous evidence on the essential role of accessible mental health services and social support in times of war, as well as the deteriorative effect of trauma exposure and forcible taking refuge on subjective well-being.
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Mariana Velykodna, Olha Charyieva, Natalia Kvitka, Kateryna Mitchenko, Oksana Shylo and Oksana Tkachenko
This study aims to develop and test multivariable psychosocial prediction models of perceived post-traumatic stress disorder (PTSD) and complex post-traumatic stress disorder…
Abstract
Purpose
This study aims to develop and test multivariable psychosocial prediction models of perceived post-traumatic stress disorder (PTSD) and complex post-traumatic stress disorder (CPTSD) symptoms development among trauma-exposed Ukrainian adults (n = 761) after 1.5 years of the 2022 Russian invasion of Ukraine.
Design/methodology/approach
This research was designed as a survey in line with the methodology of “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The survey included a questionnaire on sociodemographic characteristics and specifics of trauma exposure, as well as validated self-reported inventories: The International Trauma Questionnaire, Acceptance and Action Questionnaire – version 2, Connor–Davidson Resilience Scale-10 and the Modified BBC Subjective Well-being Scale.
Findings
Regression analysis revealed different prediction models for PTSD and CPTSD symptoms, explaining 18.4% and 41.4% of their variance with five and eight predictors, respectively. Four variables were similar in predicting PTSD and CPTSD: war-relatedness of trauma, living with a friend, perceived physical health and regret for the past. War-relatedness of trauma the respondents were exposed to was among the strongest predictors for PTSD and CPTSD severity. However, living with a friend was almost equally strong in mitigating these mental consequences. Regret for past and lowly rated physical health were assessed as relatively weaker but statistically significant predictors in this study.
Originality/value
Upon the original theoretical framework, two psychosocial prediction models were developed for PTSD and CPTSD symptoms in a non-clinical sample of trauma-exposed Ukrainian adults.
Ewout Reitsma and Per Hilletofth
The purpose of this study is to evaluate critical success factors (CSFs) for the implementation of an enterprise resource planning (ERP) system from a user perspective.
Abstract
Purpose
The purpose of this study is to evaluate critical success factors (CSFs) for the implementation of an enterprise resource planning (ERP) system from a user perspective.
Design/methodology/approach
The research was conducted in two successive steps. First, a literature review was conducted to derive CSFs for ERP system implementation. Second, a survey was conducted to evaluate the importance of these CSFs from a user perspective. Data were collected through a questionnaire that was distributed within a German manufacturer and was developed based on the CSFs found in the literature. Gray relational analysis (GRA) was used to rank the CSFs in order of importance from a user perspective.
Findings
The findings reveal that users regard 11 of the 13 CSFs found in the literature as important for ERP system implementation. Seven of the CFSs were classified as the most important from a user perspective, namely, project team, technical possibilities, strategic decision-making, training and education, minimum customization, software testing and performance measurement. Users regarded 2 of the 13 CSFs as not important when implementing an ERP system, including organizational change management and top management involvement.
Research limitations/implications
One limitation of this study is that the respondents originate from one organization, industry and country. The findings may differ in other contexts, and thus, future research should be expanded to include more organizations, industries and countries. Another limitation is that this study only evaluates existing CSFs from a user perspective rather than identifying new ones and/or the underlying reasons using more qualitative research.
Practical implications
A better understanding of the user perspective toward CSFs for ERP system implementation promises to contribute to the design of more effective ERP systems, a more successful implementation and a more effective operation. When trying to successfully implement an ERP system, the project team may use the insights from the user perspective.
Originality/value
Even though researchers highlight the important role users play during ERP system implementation, their perspective toward the widely discussed CSFs for ERP system implementation has not been investigated comprehensively. This study aims to fill this gap by evaluating CSFs derived from the literature from a user perspective.
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Leandro dos Santos, Elsebeth Holmen, Ann-Charlott Pedersen, Maria Flavia Mogos, Eirin Lodgaard and Daryl John Powell
Toyota had mature lean capabilities when developing its supplier network. This paper aims to explore how companies can develop a Toyota-style supplier network (TSN) while their…
Abstract
Purpose
Toyota had mature lean capabilities when developing its supplier network. This paper aims to explore how companies can develop a Toyota-style supplier network (TSN) while their lean capabilities are still evolving.
Design/methodology/approach
Theoretically, this paper relies on the literature on lean maturity levels and lean supplier network development. Empirically, the paper portrays a Toyota-style initiative, detailing the buyer’s efforts to develop internal lean capabilities concurrently with developing lean in its supplier network. It compares the Network for supplier innovation (NSI) initiative with TSN development regarding activities, organizations and knowledge-sharing routines.
Findings
Unlike the sequential development in the case of Toyota, NSI improved performance and capabilities in the buyer’s supplier network by implementing lean in the firm and its supplier network concurrently. Third-party involvement was the key to the initiative’s success.
Research limitations/implications
The findings are based on an in-depth single-case study which allows theoretical generalization but not statistical generalization. Furthermore, the case study concerns an initiative with Norwegian firms during a financial recession. Future studies should consider these limitations on how firms with evolving lean capabilities can develop a TSN-style supplier network and the importance of involving third parties operating in the role of lean master.
Practical implications
This study suggests what buying firms should consider when designing a TSN initiative, enrolling suppliers and engaging third parties that can take on the role of lean master.
Originality/value
Previous research has focused on how mature lean firms develop lean suppliers and networks. This paper extends this to firms whose lean capabilities are still evolving.