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1 – 4 of 4Ahmad Albqowr, Malek Alsharairi and Abdelrahim Alsoussi
The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of…
Abstract
Purpose
The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.
Design/methodology/approach
This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.
Findings
This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.
Research limitations/implications
The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.
Originality/value
This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.
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Kai Hänninen, Jouni Juntunen and Harri Haapasalo
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive…
Abstract
Purpose
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.
Design/methodology/approach
Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.
Findings
Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.
Research limitations/implications
The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.
Practical implications
This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.
Originality/value
This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.
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Parikshit Joshi, Anshu Singh, Garima Joshi and Preeti Singh
In the knowledge management (KM) literature, there are umpteen discussions on knowledge sharing; however, the scholarly community still faces a dearth of literature on knowledge…
Abstract
Purpose
In the knowledge management (KM) literature, there are umpteen discussions on knowledge sharing; however, the scholarly community still faces a dearth of literature on knowledge hiding behavior (KHB) and its determinants. The current study aims to examine the direct effect of dark triad (DT) personality dimensions (machiavellianism, narcissism and psychopathy) on KHB dimensions (rationalized hiding, evasive hiding and playing dumb). Drawing on social control theory, this study also explores the moderating effect of workplace spirituality (WS) on the direct relationship between DT and KHB.
Design/methodology/approach
Using purposive sampling, 281 matched-pair datasets from faculty members working with higher education institutions (HEI) in India have been obtained. The direct relationship has been tested through regression analysis and moderation analysis has been performed using the PROCESS macro for SPSS.
Findings
The study has successfully mapped DT dimensions with KHB dimensions, and it is observed that machiavellians mostly use evasive hiding, narcissists believe in rationalized hiding and paying dumb is mostly used by psychopaths. Workplace spirituality (WS) weakens the direct relationship between DT and KHB.
Practical implications
HEIs are advised to foster a climate conducive to WS by getting faculty to realize that their job is something larger than themselves through developing a sense of community among faculty members.
Originality/value
This empirical study extends the KM literature and expands the scope of bridging the gaps on KHB. It is one of the few studies to examine the impact of DT on KHB with WS as a moderator in HEIs.
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Mariam Kawafha, Duaa Al Maghaireh, Najah Shawish, Andaleeb Abu Kamel, Abedelkader Al Kofahi, Heidar Sheyab and Khitam Alsaqer
This study aims to enhance understanding of malnutrition's effect on academic achievement of primary school students.
Abstract
Purpose
This study aims to enhance understanding of malnutrition's effect on academic achievement of primary school students.
Design/methodology/approach
This is a descriptive, cross-sectional design built on Roy's adaptation model (RAM). This study uses a random cluster sample, consisting of 453 primary school students. Contextual stimuli (mother's educational level, income and child’s breakfast eating) and focal stimuli (wasting, thinness, body mass index and stunting) were examined regarding adaptive responses to student’s academic achievement.
Findings
The investigation revealed that Model 1, which took into account factors of age, gender, the frequency of breakfast, income, the number of family members and the education of mothers, explained 12% (R2 = 0.12) of the variance in academic achievement. Stuntedness (β = −3.2 and p < 0.01), BMI (β = 0.94 and p < 0.001), family income per month (β = 5.60 and p < 0.001) and mother's education (β = 2.79 and p < 0.001) were the significant predictors in Model 2.
Practical implications
This study provides evidence that malnutrition is associated with ineffective academic achievement. Moreover, variables such as the mother's level of education, family income and the child’s breakfast consumption have a significant impact on academic achievements.
Originality/value
RAM is a useful framework for determining factors affecting people's reactions to difficult circumstances.
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