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The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.

Within the scope of the research, articles about service robots were examined by the systematic review method.

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.

This study aims to investigate how Citation Gecko technology might help libraries provide better research support services. The paper explains specifically how Citation Gecko can help libraries provide more precise and thorough references, save time and enable methodical literature reviews and scoping studies amid the constantly evolving nature of research domains. The paper also considers how businesses and libraries can gain from implementing the technology.

The paper’s conceptual study of the function of librarians in assisting researchers – particularly in the setting of exhaustive literature reviews and scoping studies – forms the foundation of the piece. The authors talk about the difficulties in guaranteeing the authenticity and comprehensiveness of the literature review process and the significance of adopting tools like Citation Gecko to help with this process. The possible adoption of Citation Gecko in libraries is also forecasted using the technological adoption model paradigm.

Libraries that use Citation Gecko technology provide better research support services by providing accurate and comprehensive references, saving time and assisting systematic literature surveys and scoping studies. The tool is simple to use and does not require professional training due to its user-friendly interface and ability to produce references fast. Using Citation Gecko technology can enhance libraries’ capacities to support researchers, faculty and students in their research projects by making a significant contribution to systematic surveys and referencing efforts.

This study adds to the continuing discussion about how libraries may use technology to improve the services they provide to users who need research support. It had never been looked into how citation Gecko might help libraries with their reference and systematic review study offerings.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.

Africa's business environment (BE) is characteristically unfriendly and poses severe development challenges. This study evaluates the impact of business climate on productivity in sub-Saharan Africa (SSA).

Macroeconomic data for 51 sub-Saharan African economies from 1990 to 2018 are employed for the analysis. The seemingly unrelated regression model is used to address inter-sectorial linkages.

The study uncovers several findings. First, a high start-up cost substantially leads to productivity losses by limiting the funds available for investment in productivity-enhancing labour and technology and limiting the number of businesses that see the light of day. The productivity impacts of start-up costs are most enormous for industry, followed by services and agriculture. Second, economies with favourable financing environments tend to be more productive economy wide and sector wise. Third, high taxes and tax inefficiency lower productivity by reducing the resource envelope of firms, thus lowering investment amounts. Fourth, poor business infrastructure inflicts the most damage on productivity. Lastly, business administration and macroeconomic environments impact sectoral and economy-wide productivity.

SSA economies must strive to lower the cost of starting a business as high start-up costs injure productivity. One way of reducing start-up costs is to create a one-stop shop for registering and formalising a business. Another way is to automate business registration and administrative processes to reduce red tape and corruption.

The authors extend the body of knowledge by analysing sectoral and economy-wide productivity effects of various business climate indicators while accounting for inter-sectoral linkages, cross-sectional dependence and endogeneity.

The primary objective of this study aims to intensively explore the environment of Indonesian regulations and laws related to the Islamic banking system and micro-, small- and medium-sized enterprises (MSME) and unveil the restrictive laws and regulatory flaws that potentially hinder the Islamic banking institution and MSME industry in achieving financial inclusion and promoting sustainable growth.

This paper implements a qualitative method by implementing a multi-case study research strategy, both from the Islamic banking institutions and the MSME industries. The data were gathered primarily through an interview approach by adopting purposive uncontrolled quota sampling.

The findings of this paper reveal two essential issues: First, the regulatory imbalances and restrictions could demotivate and hinder the efforts of Islamic banks in providing access to finance for the MSME segment, hence, encumbering the achievement of the financial inclusion agenda from the Islamic banking industry. Second, the flaws in MSME registration and taxation might discourage the formal MSMEs from extending their business license and prevent the informal MSME units from registering their business. This issue would potentially lower their chance of accessing external financing from the formal financial institutions and participating in supportive government programmes due to the absence of proper legality.

Since this paper only observed six Islamic banks and 22 MSME units in urban and rural locations in Indonesia using a case study approach, the empirical findings and case discussions were limited to those respective Islamic banks and MSME participants.

By referring to the recommendations as presented in this paper, two critical policy implications could be expected from adopting the proposed recommendations, among others: By addressing the issues of the regulatory imbalance associated with the Islamic banking industry and introduce the deregulatory policies on profit and loss sharing (PLS) scheme implementation, this approach will motivate the Islamic banking industry in serving the MSME sector better and provide greater access to financial services, particularly in using the PLS financing schemes. By resolving the problems on MSME registration and taxation, this strategy will enhance the sustainability of the formal MSMEs’ operation and encourage the informal ones to register, hence, improving their inclusion into the formal financing services and government assistance programmes.

The present study attempts to address the literature shortcomings and helps to fill the gaps – both theoretical and empirical – by incorporating the multi-case study among Indonesian Islamic banks and MSMEs to extensively explore the Indonesia regulatory environment pertaining to the Islamic banking system (supply-side) and MSMEs (demand-side), and thoroughly investigates and reveals the restrictive laws and regulatory flaws that could potentially hinder the Islamic banking institutions and MSME industries in attaining financial inclusion and contributing to sustainable development.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.