Navigating Workforce Localization and Operational Challenges in Oman’s Logistics Sector: A Case Study

The Internet of Things (IoT) has resulted in substantial advances in the logistics sector, particularly in logistics storage management, communication systems, service quality, and supply chain management. The goal of this study is to create an intelligent supply chain (SC) management system that provides decision support to SC managers in order to achieve effective Internet of Things (IOT)-based logistics. Current research on predicting risks in shipping operations in the logistics sector during natural disasters has produced a variety of unexpected findings utilizing machine learning (ML) algorithms and traditional feature-encoding approaches. This has prompted a variety of concerns regarding the research’s validity. These previous attempts, like many others before them, used deep neural models to gain features without requiring the user to maintain track of all of the sequence information. This paper offers a hybrid deep learning (DL) approach, convolutional neural network (CNN) + bidirectional gating recurrent unit (BiGRU), to lessen the impact of natural disasters on shipping operations by addressing the question, “Can goods be shipped from a source location to a destination?”. The suggested DL methodology is divided into four stages: data collection, de-noising or pre-processing, feature extraction, and prediction. When compared to the baseline work, the proposed CNN + BiGRU achieved an accuracy of up to 94%.

Workforce localization (WL) has become an issue of increasing importance in the Arab Gulf region, a key emerging market, where, in many cases, local citizens are the minority in terms of population, and compete with high numbers of expatriate employees for jobs and positions. The purposes of this paper are to empirically explore recruitment and selection (R&S) challenges and practices related to WL in the UAE, and to compare and contrast these between private and public sector organizations. This paper adopts a qualitative, inductive methodology. Data were collected using semi-structured interviews with HR/ Localization managers in five private (PVO) and six public organizations (PSO) in the UAE, in different industrial sectors. Data were analyzed using NVivo 10 software. First, we found that both PVOs and PSOs face six common challenges related to the R&S of local candidates: 1) the lack of relevant education, skills and experience of Emirati Applicants (EA), 2) their high compensation expectations, 3) their lack of business, industry and career awareness, 4) competition from other employers, 5) some sector- and job-person fit considerations and 6) resistance from expatriates. Second, we found that both PVOs and PSOs have dedicated recruitment methods to attract EAs. Both PVOs and PSOs developed and communicated employee value propositions for EAs, used proactive, targeted, diversified internal and external recruitment methods, and evaluated the effectiveness of their recruitment practices, using established quantitative and qualitative measures. We found some differences between PVOs and PSOs: PSOs tended to reserve specific positions for local employees, used more targeted external recruitment methods and more numerous effectiveness evaluation measures than PVOs. Third, at the selection stage, we found that all organizations reviewed their job descriptions and selection processes to avoid any discriminatory items, most of them organized inclusive, culturally trained staffing committees. Most of the PSOs intensively modified their selection processes (e.g. using modified screening, selection criteria and standards, and selection steps) to facilitate WL, whereas PVOs only modified experience requirements for EAs. Both PVOs and PSOs used similar testing, interviewing processes and effectiveness evaluation measures, although PSOs generally utilized a greater range and number. While our findings on R&S practices showed similarities between PVOs and PSOs, they also highlighted a number of differences. This paper contributes to expanding the scope of understanding of the staffing processes in a non-Western context, adding to the body of empirical literature on localization, R&S, and public sector HRM in the Arab Middle East and Gulf countries. Implications for further research, practitioners and policy makers involved in WL are discussed.

The concept paper explores the transformative potential of technology in enhancing the logistics and supply chain sector to bolster the UK's economic competitiveness. This executive summary highlights the paper's primary objectives, theoretical frameworks, and anticipated outcomes, focusing on the integration of advanced technologies to streamline supply chain operations and drive economic growth. This paper aims to provide a comprehensive framework for understanding how technology can be leveraged to optimize logistics and supply chain management in the UK. It underscores the importance of a robust and efficient supply chain as a cornerstone of economic competitiveness, enabling businesses to reduce costs, improve delivery times, and enhance overall operational efficiency. Central to this paper is the exploration of various technological innovations that can revolutionize supply chain management. It discusses the impact of emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data analytics on the logistics sector. These technologies enable real-time tracking, predictive analytics, enhanced transparency, and improved decision-making processes, which are crucial for maintaining a competitive edge in the global market. The paper delves into theoretical models and frameworks that support the integration of technology into supply chain management. It examines concepts such as the Digital Supply Chain (DSC) model, which emphasizes the interconnectedness of digital technologies in creating a seamless supply chain network. Additionally, the paper explores the Supply Chain Operations Reference (SCOR) model, which provides a structured approach to measuring and improving supply chain performance through technology-driven metrics and best practices. Addressing the practical challenges of implementing tech-driven logistics, the paper highlights issues such as cybersecurity risks, high initial investment costs, and the need for skilled labor. It proposes solutions like fostering public-private partnerships, investing in cybersecurity measures, and developing training programs to build a tech-savvy workforce capable of managing advanced supply chain systems. The expected outcomes of tech-driven logistics and supply chain management include increased operational efficiency, reduced operational costs, improved customer satisfaction, and enhanced agility in responding to market changes. These improvements can significantly contribute to the UK's economic competitiveness, positioning it as a leader in the global supply chain landscape. The paper provides a strategic roadmap for integrating advanced technologies into the logistics sector. By leveraging these technologies, the UK can enhance its supply chain efficiency, drive economic growth, and maintain a competitive advantage in the global economy. The paper calls for concerted efforts from policymakers, industry leaders, and academia to foster an environment conducive to technological innovation and supply chain excellence. Keywords: Logistic, Supply Chain, Technology, Cyber Security, UK.

Lojistik sektörü dünyada ve Türkiye’de giderek büyümekte ve sektörün potansiyeli zamanla daha iyi anlaşılmaktadır. Lojistik sektörünün gelişime oldukça açık olduğu, teknoloji ile ortaya çıkan yeniliklere ayak uydurmak zorunda olduğu bilinmektedir. İşletmeler bu yeniliklere ayak uydurarak, rekabette başarılı olmaya çalışmaktadır. Endüstri 4.0 özellikle lojistik gibi rekabetin ön planda olduğu sektörleri etkisi altına almıştır. Yapılan son araştırmalarda yapay zeka tekniklerinin kullanımında büyük oranda artış olduğu görülmektedir. Yapay zekanın lojistik sektöründe kullanılması sonucunda özellikle işleyiş ve dinamiklerde değişiklikler oluşmaya başlamıştır. Yapay zeka, insan zekasının fizyolojik ve nörolojik yapısını çeşitli teknolojiler yardımı ile modelleyerek makinelere aktarmaktadır. Yapay zeka ile birlikte ortaya çıkan sürücüsüz araçlar, depolama ve raflarda kullanılan robotlar, sistem içerisinde büyük verilerin rahatlıkla kullanılması gibi seçenekler lojistik sektöründeki hataların en aza indirgenmesini sağlamaktadır. Lojistik sektöründe yapay zeka kullanımı sayesinde işletmeler daha verimli işler ortaya koymaktadır. Yapılan bu çalışmada, lojistik sektöründe kullanılan yapay zeka ve makine öğrenmesi uygulamalarının geniş bir perspektif ile incelenmesi amaçlanmıştır. Çalışmada önce yapay zeka ve makine öğrenimi kavramları açıklanmış ardından endüstri ve lojistik kavramlarına değinilerek lojistikte kullanılan yapay zeka ve makine öğrenmesi uygulamalarına yer verilmiştir. Küresel lojistik ve tedarik zinciri yönetimi konusunda yapay zekanın günden güne kendini geliştirdiği ve lojistik süreçleri kolaylaştırdığı görülmektedir.

Future innovations in logistics and supply chain management are driven by technological, regional, economic and social changes as well as sustainability and resource restrictions. They will not occur without sufficient attention for the human contribution, in particular the qualification, competence and motivation of the workforce in the logistics domain. Worldwide, about 50 million people—or the entire population of South Korea—are employed in the SCM, logistics and transportation sectors. Consequently, human resource and knowledge management plays an important role, more so when considering demographic developments (ageing, migration) and increasing globalization. Whereas in the past, many blue-collar jobs in logistics such as truck driving merely required a basic school education and rudimentary qualification levels, these jobs now require increased competences due to improved technology interaction, e.g., barcode and RFID systems, fleet management or toll and truck steering concepts and finally artificial intelligence applications. The same is true for many white-collar jobs in logistics, exemplified by the increasing number of university graduates employed in the sector. This is especially true for specific fields such as logistics information technology, contract logistics and supply chain innovation and design, which in turn leads to the question of how to assess qualitative and quantitative competence levels in the SCM and logistics sector. Such an analysis example is provided here with the Berufswertigkeit concept (reference framework for competence levels). This may lead to a new paradigm in HR and knowledge management for SCM and logistics: whereas past education was mainly driven by formal qualifications and therefore personnel groups (white-collar/blue-collar), future concepts may focus on an individual analysis of gaps and potentials based on elaborate evaluations. In addition, modern concepts like edugaming are outlined as examples for future qualification and training concepts for logistics personnel.

Purpose - This paper aims to identify the Critical Success Factors (CSFs) for the Big Data adoption in Morocco's Transport and Logistics Sector (TLS) through an exploratory case study of Moroccan Logistics Service Provider (LSP) specializing in Big Data and Analytics consulting for Logistics and Supply Chain Management (SCM). Design/methodology/approach - This paper utilized a qualitative method of research using an exploratory case study, employing interviews, observation of the areas of intervention, and several services and projects provided by LSP. A semi-structured interview was conducted to provide opinions on the use of Big Data Analytics (BDA) and to explore the influential CSFs on Big Data adoption in Morocco's TLS. Findings - Based on the exploratory case study, we outline some suggestions related to the challenges and obstacles to Big Data adoption in Morocco's TLS. Some of these suggestions are in line with what the literature survey has been examining. Originality/value - This paper provides two original contributions. The first contribution is to identify the influential key factors for a Big Data project's success in Morocco's TLS. The second contribution asks specifically about the role of LSPs in stimulating the Big Data adoption in Morocco's TLS.

This paper addresses a key social–cultural aspect of sustainability in the Gulf region: Workforce localization (WL). Our research objective is to empirically explore organizational socialization (OS) practices in the context of WL in the United Arab Emirates (UAE), where National Citizens (NCs) are a powerful minority in the workforce. This research adopts a qualitative methodology, using semi-structured interviews with managers in charge of the WL program in 14 organizations in the UAE, across different industrial sectors and ownership. We found five major OS practices: Establishing thorough orientation programs, providing formal training programs (skills, diversity/cultural awareness, supervisor, mentoring and coaching team building), redesigning NCs’ jobs and work teams, engaging expatriates in NCs’ OS processes, and organizing networking events. All organizations rigorously evaluated the effectiveness of their OS practices. This study contributes to the empirical literature on management OS, WL, and diversity management in a non-western, emerging Arab country. It contributes to theory development on the content of OS practices, showing how a minority can be a powerful group around whom socialization processes are tailored to integrate them fully into the organization. Practically, our findings inform managers of how to adapt their existing OS practices to the specific needs of minority members, and support Gulf Cooperation Council (GCC)-based organizations and policymakers with the design, monitoring, and implementation of WL programs, and with the development of a sustainable workforce.

PurposeConventional wisdom posits that firms in slow clockspeed industries usually favor exploitation over exploration, prioritizing the need to increase efficiency, reduce costs and invest in process improvements. However, what happens when such firms face structural changes in the long run? The authors claim that even firms in slow clockspeed industries should be ambidextrous, that is, they should develop both exploration and exploitation capabilities. Supply chain (SC) managers are key players in enabling organizational ambidexterity. This paper aims to identify the abilities that characterize the ambidextrous SC managers.Design/methodology/approachThe authors collected data from an in-depth case study through ethnographic research, non-participant observation and interviews with SC managers at a Brazilian chemical firm embedded in a slow clockspeed network of clients. These longitudinal data were used to demonstrate the process of implementing new projects in an SC department.FindingsThe authors propose a set of key abilities that enable ambidexterity in SC managers for them to contribute effectively to the SC exploration and exploitation practices: a holistic yet focused view; prior experience in multiple functional areas; technical knowledge; openness towards network connectivity; openness to sharing ideas with other managers; empathy; and entrepreneurial capabilities.Research limitations/implicationsThis paper contributes to the SCM ambidexterity literature by bringing to light the abilities of successful ambidextrous SC managers. The seven abilities identified are discussed. The authors formulate theoretical propositions on how these abilities enable SC managers’ ambidexterity.Practical implicationsThis study provides SC managers with the knowledge of a set of individual abilities they should develop among their SC personnel to offer a more suitable environment in their departments for ambidexterity to take place. In addition, these abilities can be used as screening criteria in personnel selection processes to increase the proportion of ambidextrous employees within the firm. The identified characteristics could also be used as recruitment criteria for managerial positions in SCM.Originality/valueThis research advances SC literature by studying SC managers through the lens of the organizational ambidexterity literature. Using a combination of case study, non-participant observation and ethnographic research, the authors derive a set of propositions for the characteristics of ambidextrous SC managers.

Noncompliance with employment and labor laws can result in compensatory and punitive damages, adversely impacting business profitability. Human Resources (HR) personnel who lack strategies to anticipate and react to changes in employment laws risk penalties for noncompliance, resulting in reduced profitability. Grounded in the top-down model of adaptation and political risk management, the purpose of this qualitative multiple case study was to explore strategies some HR personnel use to anticipate and react to changes in employment laws, to avoid compensatory and punitive damages. The participants included nine HR personnel from nine organizations located in the District of Columbia, Maryland, and Virginia tristate area who implemented successful strategies to align with mandated legislation and other existing and new employment laws. Data were collected using semistructured interviews and review of company documents related to applicable labor laws. Thematic analysis was used to analyze the data. Three themes emerged: (a) strategies to anticipate and react to changes in employment laws; (b) strategies to anticipate and react to changes in “ban the box” legislation; and (c) obtaining feedback on reacting to changes in employment laws. Key recommendations include: (a) providing employment law compliance education and training programs for all supervisors and HR staff; (b) changing the company culture and values, beginning with upper management; and (c) collaborating with the legal team to ensure compliance. The implication for positive social change includes increased employment among marginalized members of society, including persons with criminal histories, which may reduce crime rates, recidivism, and reliance on government assistance programs.

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The rapid development of blockchain technology and its potential for addressing transparency, security, and efficiency challenges in supply chain management is attracting significant attention from both academics and the business community. The growing number of blockchain solutions for supply chain management requires systematization and categorization for better understanding of their capabilities and limitations. The object of research is existing blockchain solutions and their applications in supply chain management. The subject of research is the methods, architectures, and technological features of implementing blockchain technologies in supply chain management systems. The aim of this work is to develop a comprehensive blockchain architecture for a solution that could be classified as a general partially distributed supply chain management system solution and to determine key characteristics and criteria for their effectiveness. A comparative analysis of existing solutions has been conducted, and their advantages and disadvantages have been identified. Recommendations have been developed for selecting optimal blockchain solutions for different types of supply chains. Conclusion: the conducted research has allowed for the systematization of existing blockchain solutions for supply chain management and the creation of a structured system for their categorization. Key industry development trends and promising directions for blockchain technology implementation have been identified. The research results can be used in selecting and implementing blockchain solutions across various industries and logistics sectors.

This study investigates the factors influencing the implementation of blockchain in logistics in the United Arab Emirates (UAE), including security, privacy, end-user benefits, quality control, technology infrastructure, and lack of general awareness. A mixed-methods approach was used, with data collected through survey questionnaires and semi-structured interviews. The research targeted logisticians in the UAE's supply chain department, using random probability sampling and a sample size of 151 for surveys and using purposive sampling for recruiting 10 experts. Using SPSS 24.0, the Pearson Correlation analysis revealed a strong association between blockchain in logistics and IT infrastructure and awareness of blockchain in the UAE logistics sector. Exploratory factor analysis showed a significant difference towards the security of data in the implementation of blockchain in the logistics sector in the UAE. This research suggests that implementing blockchain technology in UAE logistics companies can enhance data security and quality control, influencing managers’ decisions positively and recommends prioritizing data security and quality control. The study's geographical context emphasizes its contribution in the research area showing the importance of considering cost, benefits, security, IT infrastructure ownership, and awareness aspects in the adoption of blockchain technology in supply chain management.

Purpose– This study aims to develop a theoretical model that specifies the most important factors hypothesised to facilitate reciprocal knowledge transfer between nationals and non-nationals in the context of workplace quotas.Design/methodology/approach– Expatriate labour is viewed as a form of contingent employment that provides firms with ready access to experienced and specialised knowledge. We argue that in a knowledge economy, the successful use of workplace quotas for nationals depends on effective management of both nationals and non-nationals. By drawing on scholarly contributions in the areas of strategic management, agency theory, knowledge management and absorptive capacity, this paper consolidates extant knowledge and proposes a new framework aimed at developing a more integrated agenda for future research.Findings– Three broad categories are posited as strategic enablers to effective knowledge management. First, senior leadership has a direct role in developing appropriate policies, promoting transparency and fostering a culture of trust and an indirect role through the establishment of incentives. Second, the influence of incentives on both knowledge management and process improvement is addressed. Third, the characteristics of each group with regard to qualifications, motivation and receptivity are discussed. Optimally, these factors work in concert to build competencies that ultimately satisfy customers and meet organisational goals.Originality/value– There is a gap in scholarly research that explicitly links important organisational and management concepts to the study of expatriate-national interactions. This article contributes to understanding how policy makers and leaders can strengthen the transformative forces that will drive successful development of human capital.

Logistics has been recognized as an important weapon for competitive advantage to boost economic growth. This paper examines the integration in the logistics sector that may result in increasing the economic growth. The study is also considering the role of government policy on the relationship between the factors of integration and the economic growth. The finding of this study shows that there is positive effect of: (1) Infrastructure on economic growth, (2) productivity on economic growth, (3) competiveness on economic growth, (4) Technological Advancement on economic growth. This study also found that (5) The Relationship between infrastructure, productivity, competiveness, technological advancement on economic growth moderated by government policies.

The development of Industry 4.0, a new digital industrial technology, has a favorable effect on how well the supply chain functions. Big Data, Social Media, and the Internet of Things (IoT) have all been proposed as ways to enhance supply chain performance. Although there has been limited exploratory research in this area, the favorable impact of the Internet of Things (IoT), Social Media, and Big Data on Supply Chain on supply chain and company performance has been empirically confirmed. How the logistics sector is being impacted by Big Data, IoT, and Social Media from a business and customer perspective? Can the Supply Chain be managed and controlled more effectively because of the integration of social media and ICT? Does Supply chain management get better with the incorporation of information and communication technology? The initial goal of this study is to demonstrate the connection that already exists between supply chain management, social media, big data, and the internet of things. Second, we'll discuss how the integration of social media, big data, and the internet of things has affected the sustainability, efficiency, and various flows of supply chain management.