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1 – 10 of 11Majid Rahi, Ali Ebrahimnejad and Homayun Motameni
Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is…
Abstract
Purpose
Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.
Design/methodology/approach
The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.
Findings
The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.
Research limitations/implications
By expanding the dimensions of the problem, the model verification space grows exponentially using automata.
Originality/value
Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.
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Huda Hussain and Marne De Vries
This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely…
Abstract
Purpose
This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.
Design/methodology/approach
A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.
Findings
The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.
Originality/value
The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.
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Satyendra Kr Sharma, Rajkumar Sharma and Anil Jindal
Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This…
Abstract
Purpose
Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.
Design/methodology/approach
Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.
Findings
It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.
Originality/value
This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.
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Yanhao Sun, Tao Zhang, Shuxin Ding, Zhiming Yuan and Shengliang Yang
In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to…
Abstract
Purpose
In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.
Design/methodology/approach
First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.
Findings
The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.
Originality/value
This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.
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Mehreen Malik, Muhammad Mustafa Raziq, Naukhez Sarwar and Adeel Tariq
Scholars and practitioners acknowledge that digital leadership can help organizations gain a competitive advantage. This article focuses on the characteristics, styles and skills…
Abstract
Purpose
Scholars and practitioners acknowledge that digital leadership can help organizations gain a competitive advantage. This article focuses on the characteristics, styles and skills needed for effective digital leadership. It looks at the role of digital leaders in innovating business models and introducing organizational change required for a successful digital transformation.
Design/methodology/approach
This paper is based on a comprehensive literature review of digital transformation, digital leadership, business model innovation, and organizational culture. It draws on institutional theory (INT) the neo-institutional theory (NIT). It draws from Science Direct, Web of Science and Google Scholar publications. A proposition and a conceptual framework are developed based on evaluating and synthesizing the literature.
Findings
We find that specific leader characteristics (agility, participative, innovativeness and openness), styles (democratic and transformational) and skills (cognitive, social, technological and digital) enable successful business model innovation and organizational change, all of which allow successful digital transformation of firms.
Originality/value
The literature on digital transformation has not been well integrated with the leadership literature. This is particularly true in terms of the role digital leaders play in the successful digital transformation of firms. The conceptual framework and a way forward proposed in this paper introduce future research directions on the topic.
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Mehreen Malik, Muhammad Mustafa Raziq, Naukhez Sarwar and Madiha Gohar
We explore the skills required for digital leadership for reshaping existing business models toward digital models. Digital leadership is pivotal in gaining a competitive…
Abstract
Purpose
We explore the skills required for digital leadership for reshaping existing business models toward digital models. Digital leadership is pivotal in gaining a competitive advantage and achieving successful digital transformation. However, little is known with regard to the underlying mechanisms related to digital leadership and transformation.
Design/methodology/approach
Data are collected through semi-structured interviews involving 20 participants from five Pakistani textile companies. Thematic analysis was employed as a data analysis tool.
Findings
Findings show that certain skills such as technological know-how, innovativeness, adaptability, ability to lead and steer, honesty, integrity, transformative vision, communication and collaboration are conducive to successful digital transformation in textile manufacturing firms. Similarly, digital leaders can significantly enhance business model innovation, create value for the firm, help develop new products (value proposition) and create Ecosystem partnerships (value network).
Originality/value
This article bridges gaps between existing literature on digital transformation and leadership. Digital leadership skills for digital transformation and the role of digital leaders in business model innovation have not been explored before. The conceptual framework is put forth, propositions are proposed and the findings offer some future research directions.
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Sofia Panagiotidou, Dimitrios Mihail and Anastasia A. Katou
This study, based on signaling theory, examines the pre-recruitment employer branding strategy during the COVID-19 pandemic. It investigates the relationship between spontaneous…
Abstract
Purpose
This study, based on signaling theory, examines the pre-recruitment employer branding strategy during the COVID-19 pandemic. It investigates the relationship between spontaneous word-of-mouth (WOM) recommendations for companies and prospective candidates' job application intentions. Specifically, the study explores serial mechanisms mediating the characteristics of company online career pages, including the perceived informativeness of online job advertisements (ads), candidates' preferences for its web approach to them and the company’s reputation.
Design/methodology/approach
Reflecting prospective candidates from students and young alumni of universities, partial least squares structural equation modeling (PLS-SEM) was employed on a sample of 737 individuals representing various fields of study from Greek universities.
Findings
The findings highlight the effectiveness of positive WOM recommendations during the initial stages of recruitment, particularly amidst COVID-19 challenges in the labor market, notably impacting young candidates. The study suggests that spontaneous WOM, originating from trustful sources, motivates job seekers to actively engage with the company’s web career channels, seeking information and favorable indications of the company’s approach toward its candidates. Positive WOM, combined with informative content and a friendly communication style, plays a critical role in shaping the company’s reputation. Consequently, this encouragement motivates individuals to start their job search efforts and consider applying for positions within the specific organization.
Practical implications
This research provides valuable empirical evidence in the pre-recruitment field, particularly in unforeseen crisis circumstances such as the COVID-19 pandemic. It examines how spontaneous, positive WOM from sources, like peers and alumni, significantly influences young job seekers' perceptions and preferences regarding the company’s career web channels as sources of information and signals about working conditions. The combination of positive WOM with informative content and a friendly communication style in the web approach plays a crucial role in shaping a positive company reputation. Consequently, this encourages candidates to consider applying for positions within the company.
Originality/value
This research contributes to pre-recruitment studies, especially amidst crises like COVID-19. It examines how positive WOM from trusted sources like peers and alma mater alumni influences young job seekers' views on the company’s career web channels. By emphasizing the importance of combining positive WOM with informative web content and a friendly communication style, the study offers insights into effective recruitment strategies. It highlights the significance of positive and spontaneous WOM in attracting young talent and its impact on job seekers' decision-making, even in uncertain conditions. Overall, it advances recruitment practices for attracting candidates.
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The purpose of this article is to investigate on changes of the microbial load and the chemical and physical properties of date fruits stored for 6 months under two different…
Abstract
Purpose
The purpose of this article is to investigate on changes of the microbial load and the chemical and physical properties of date fruits stored for 6 months under two different temperatures.
Design/methodology/approach
A composite sample of 100 kg date fruits from the Khalas variety, season 2019, was collected from the local market in Al Ahsa Province, Saudi Arabia, packaged in 1 kg lots, stored at room and refrigerator temperatures and the microbial contamination and the chemical and physical properties monitored over a period of six months of storage. Total bacteria, lactic acid bacteria, Enterobacteriaceae, yeasts and molds were counted and representatives of yeast and mold contaminants were identified using morphological, physiological and molecular typing techniques. Changes in the color and texture of the samples were also monitored during storage.
Findings
The yeasts detected were two strains of each of Lachancea thermotolerans and Rhodosporidiobolus fluvialis and one strain of Cystofilobasidium lacus-mascardii. For molds, one strain of each of Aspergillus niger, Aspergillus flavus, Penicillium chrysogenum and Aspergillus caespitosus have been detected. No significant growth of these microorganisms was observed, but enough load persisted during storage that makes the samples not meeting the microbiological standards. There were significant changes in the color and texture of the fruits during storage.
Originality/value
These findings add important information that can help producers and processors to improve quality and promote marketing of date fruits, especially to international markets.
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Isaac Akomea-Frimpong, Jacinta Rejoice Ama Delali Dzagli, Kenneth Eluerkeh, Franklina Boakyewaa Bonsu, Sabastina Opoku-Brafi, Samuel Gyimah, Nana Ama Sika Asuming, David Wireko Atibila and Augustine Senanu Kukah
Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of…
Abstract
Purpose
Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.
Design/methodology/approach
Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.
Findings
The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.
Research limitations/implications
For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.
Practical implications
This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.
Originality/value
This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.
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Maximilian Valta, Yannick Hildebrandt and Christian Maier
Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the…
Abstract
Purpose
Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.
Design/methodology/approach
In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.
Findings
The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.
Originality/value
This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.
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