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This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

Cost transparency is of central importance to reach a consensus between supply chain partners. The purpose of this paper is to contribute to the instrument of cost analysis which supports the link between buyers and suppliers.

Based on a detailed literature review in the area of cost analysis and purchasing, intelligent decision support systems for cost estimation are identified. Subsequently, expert interviews are conducted to determine the application possibilities for managers. The application potential is derived from the synthesis of motivation, identified applications and challenges in the industry. Management recommendations are to be derived by bringing together scientific and practical approaches in the industry.

On the one hand, the results of this study show that machine learning (ML) is a complex technology that poses many challenges for cost and purchasing managers. On the other hand, ML methods, especially in combination with expert knowledge and other analytical methods, offer immense added value for cost analysis in purchasing.

Digital transformation allows to facilitate the cost calculation process in purchasing decisions. In this context, the application of ML approaches has gained increased attention. While such approaches can lead to high cost reductions on the side of both suppliers and buyers, an intelligent cost analysis is very demanding.

The purpose of this paper is to achieve a collective understanding of the capabilities required for digital procurement transformation (DPT).

The authors contextualize theory about dynamic capabilities (DCs) to integrate the fragmented body of literature on procurement digitalization by means of a systematic literature review (SLR). By extracting and clustering capabilities, as well as proven performance outcomes from existing literature in the field, the authors develop a conceptual model of the DCs required for DPT.

The authors first introduce and define DPT and the corresponding motivations that trigger firms to invest in advanced digital technologies. Second, by adopting the DC lens, the authors provide an overview of nine microfoundations required for DPT and highlight the strategic options procurement leaders can use when strategizing about adopting combinations of digital technologies. Third, the authors present a future research agenda on DCs for DPT.

The developed conceptual model must be verified and enhanced through further empirical research.

The conceptual model can be used by procurement leaders as a starting point and framework when strategizing about digitally transforming the procurement organization.

The study is the first to synthesize previous research findings on procurement digitalization through an SLR in order to develop a fine-grained conceptual model that supports practitioners and researchers alike in better understanding the capabilities required for and potential performance outcomes of DPT.

The enabling technologies that emerged from information technology (IT) have had a considerable influence upon the development of marketing tools, and marketing has become digitalized by adopting these technologies over time. The purpose of this paper is to demonstrate the impacts of these enabling technologies on marketing tools in the past and present and to demonstrate their potential future. Furthermore, it provides guidance about the digital transformation occurring in marketing and the need to align of marketing and IT.

This study demonstrates the impact of enabling technologies on the subsequent marketing tools developed through a content analysis of information systems and marketing conference proceedings. It offers a fresh look at marketing's digital transformation over the last 40 years. Moreover, it initially applies the findings to a general digital transformation model from another field to verify its presence in marketing.

This paper identifies four eras within the digital marketing evolution and reveals insights into a potential fifth era. This chronological structure verifies the impact of IT on marketing tools and accordingly the digital transformation within marketing. IT has made digital marketing tools possible in all four digital transformation levers: automation, customer interaction, connectivity and data.

The sequencing of enabling technologies and subsequent marketing tools demonstrates the need to align marketing and IT to design new marketing tools that can be applied to customer interactions and be used to foster marketing control.

This study is the first to apply the digital transformation levers, namely, automation, customer interaction, connectivity and data, to the marketing discipline and contribute new insights by demonstrating the chronological development of digital transformation in marketing.

This study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.

A systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.

SCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.

The paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.

The main purpose of this study is to investigate the role of Industry 4.0 capability (I4.0 C) in creating a supportive environment for business model innovation by focussing on the mediating role of knowledge management capability (KMC) and the moderating effect of market uncertainty.

This paper uses interviews with managers and academics. Data were collected from 379 managers; CFA and finally regression analysis were performed, and the program “PROCESS” software was used to validate the data and examine the hypothesized relationships.

KMC mediates the relationship between Industry 4.0 capability and business model innovation. The effect of Industry 4.0 capability on KMC is stronger for firms with increased market uncertainty. In contrast, the impact of KMC on business model innovation is weaker for firms operating in highly-uncertain markets.

Data were collected at only one point in time from one country, Greece. This might pose limitations on the generalizability of our results. Future research should test the relationships examined in this study in other international contexts.

Managers should invest in more advanced technology in order to obtain knowledge and capability. In addition, they need to pay more attention to how their firms' knowledge derived from Industry 4.0 contributes to business model innovation.

The current state of knowledge of both theory and practise for critical organizational factors such as Industry 4.0 capability, KMC, business model innovation and market uncertainty will be extended.

New technological trends continue to emerge, and businesses adopt them in different capacity in a pursuit of improving current ways of doing things and to gain competitive advantages over rivals. One of the key business functions that is impacted by the implementation of different disruptive technologies is the supply chain management. As a result, there is a continuous need to identify where digitalizing supply chains may provide businesses with benefits to capitalize such gains. This study aims to examine potential impacts of digitalizing supply chains on five selected lean operations practices through the identification of key areas and benefits under each of these practices.

Data were collected from 74 participants mainly from the academic community and who were university scholars through the use of an online survey. The used online survey consists of six main parts in total, but three were included in this paper and these were designed to gather data about participants’ general information, level of influence of seven technological trends on supply chain performance and management and potential impact of digitalizing supply chains on five lean operations practices.

The authors were able to confirm the significant impact of digitalizing supply chains on the five examined lean operations practices. Most of the examined potential impacts were found to improve certain areas that directly improve the practices of the explored five lean operations practices as well as the overall supply chain and business performance. They were also able to determine the level of influence of the seven examined enabling technologies on supply chain performance and management.

To the best of the authors’ knowledge, this study is the first of its kind. Although some literature explored different aspects related to the concept of Industry 4.0 and digitalizing supply chains, no study has specifically explored potential impacts of digitalizing supply chains on lean operations. The results from this study can be beneficial to academic scholars interested in the researched themes, business professionals specializing in supply chain management and lean operations, organizations within different industrial sectors particularly manufacturing where lean thinking is adopted and any other party interested in understanding more about the impact of digitalizing supply chain on lean operations and on an overall business performance.

The purpose of this research is to study the impact of perceived adoption of Lean principles on operational performance in Lebanese pharmaceutical industries.

A quantitative method was implemented using a questionnaire that targeted 253 respondents working in eight good manufacturing practices (GMP) certified Lebanese pharmaceutical companies. Reliability analysis was performed using SPSS, and the research hypotheses were tested using regression analysis.

The results demonstrated that Lean principles positively and directly affected operational performance. It also positively affected operational performance factors of quality, cost and time. However, the analysis of each of Lean principles impact on operational performance cost was analyzed perfection, value, and value stream mapping (VSM) significantly increased operational performance. In addition, pull only positively augmented the cost reduction, whereas flow did not show any effects on any of operational performance’s factors.

In addition to enhancing operational performance, the positive effect of the perceived adoption of Lean principles on performance is also explained by managers’ efforts in studying the flow of actions in their processes to reduce wastes. To face uncertainty, training and building a workforce that is able to implement Lean principles, equipping this workforce with needed artifacts, and promoting a high-performance culture are crucial for the successful implementation of Lean principles.

Lean approach has become a major pathway of improvement especially in pharmaceutical companies. Few studies analyzed the impact of each of the Lean principles on the operational performance in companies that operate in era of uncertainty. Furthermore, the perceived adoption of Lean principles is under investigated in the Middle East in general and in Lebanon in particular.