Search results

As a key driver of organizational agility, open innovation allows for improving time-to-market and complexity, which are the mechanisms that most significantly lower the risk of knowledge expropriation in emerging markets. For this reason, there is concern about the negative impacts of hiding knowledge in the context of inter-organizational collaborative work. Therefore, the research goal is to analyze the moderating effect of the three types of knowledge hiding (playing dumb, evasive hiding and rationalized hiding) on the relationship between open innovation (both inbound and outbound) and agility.

The research model was tested with survey data from a sample of 248 companies located in an emerging country, mostly from sectors of high turbulence in demand and technology.

None of the three types of knowledge hiding has a negative effect on the relationship between open innovation and agility. Surprisingly, evasive hiding has a positive and significant effect, specifically on the relationship between inbound open innovation and agility.

The study contributes to the discussion on the contradictory influence of knowledge hiding. Although the presence of knowledge hiding in business relationships with their external partners is undeniable, this research makes clear that, when faced with the particular need to be agile, businesses recognize that the benefits of open innovation in terms of time-to-market improvement and complexity outweigh the protectionism underlying hiding. Moreover, the study results suggest evasive hiding is essential for the inbound process to use time effectively and avoid wasting it in discussions that do not promote agility.

This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.

The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.

The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.

Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.

This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

The supply chain agility (SCA) is becoming a source of competitive differentiation but debate on its antecedents which can result in optimal firm performance is still non-pervasive in the literature. Taking this gap into consideration, the current research aimed at investigating various enablers of supply chain agility of Pakistani pharmaceutical industry.

The data were collected from 204 top executives working in different supply chain functions including planning, supplying, operations and purchasing in national and multinational pharmaceutical companies in Pakistan.

Through serial-mediation model, results revealed the strength of various SCA enablers, along with the mediating roles of delivery dependability.

This study adds in the literature on how various supply chain enablers and competencies help the organizations to achieve supply chain agility and performance, especially in a developing country.

The purpose of this paper is to explore the relationship between supply chain management practices, logistics capabilities, logistics integration and competitive advantage of Small and Medium Enterprises (SMEs) in a developing country.

Using a structured questionnaire survey, cross-sectional data collected from 204 SMEs in Kampala – Uganda were analysed using exploratory and confirmatory factor analysis, and Structural Equation Modelling (SEM) using AMOS version 26 to validate the theorised relationships.

The study findings revealed that both supply chain management practices and logistics integration are positively and significantly associated with competitive advantage. Also, both supply chain management practices and logistics capabilities are positively and significantly associated with logistics integration. Additionally, the authors found that logistics integration partially mediates in the relationships between supply chain management practices and competitive advantage, and logistics capabilities and competitive advantage. Conclusively, the three independent variables collectively account for 11% variance in competitive advantage of SMEs.

Given the general observation that SMEs are fundamental to socio-economic development, yet resource constrained, this study uses Resource-based and dynamic capabilities theoretical perspectives to provide an empirical understanding of the supply chain and logistics resources and capabilities necessary for building competitive advantage of SMEs in the context of a developing economy.

The purpose of this study is to improve supplier performance and strategic sourcing decisions by integrating jobshop scheduling, inventory management and agile new product development. During the COVID-19 pandemic, the organizations have struggled a lot to maintain the supplier performance and strategic sourcing decisions in the organizational benefit. However, in this context, the organization’s agile new product development (ANPD) process must be aligned with this requirement by maintaining the inventory and jobshop scheduling. As a result, identifying ANPD indicators, performance metrics and developing a structural framework to guide practitioners at various stages for smooth adoption is essential to improve the overall performance.

A comprehensive literature review is conducted to identify jobshop scheduling, inventory management and ANPD indicators along with the performance metrics, and the hierarchical structure is developed with the help of expert opinion. The modified stepwise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assurance (WASPAS) techniques, along with expert judgement, are used in this study to calculate the weights of the indicators and the ranking of the performance metrics.

As per the weight computation by SWARA method, the strategy indicators have the highest relative weight, followed by the product design indicators, management indicators, technical indicators, supply chain indicators and organization culture indicators. According to the ranking of performance metrics obtained through WASPAS, the “frequency of new product development is at the top”, followed by “advances in product design and development” and “estimated versus actual time to market”.

It is believed that the framework developed will help industrial practitioners to plan effectively to improve supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

The outcomes of the present study will be extremely beneficial for the industry practitioners to improve the supplier performance. The indicators identified may guide the ANPD penetration, and performance metrics may be useful for evaluation and comparison.

A unique combination of modified SWARA–WASPAS technique has been used in this study which would be beneficial for organizations willing to adopt the jobshop scheduling and inventory management and ANPD for improving supply chain performance.

The purpose of this research was to study the impacts of adoption of additive manufacturing (AM) for spare parts procurement, specifically in the context of supply chain resilience (SCR) especially regarding efficient spare parts inventory management. Furthermore, key narratives in the adoption of AM toward better SCR are explored.

In-depth interviews with semi-structured open-ended questionnaire were conducted to collect primary qualitative data from 24 supply chain management (SCM) experts. Respondents consisted of experts across various industries. The data were analyzed by thematic content analysis method.

The results indicated that AM could be a suitable tool to reduce dependence on original equipment manufacturers (OEMs) for spare parts procurement. Data analysis also revealed that AM adoption might lead to significant cost and lead time reduction. Designs protected as intellectual properties (IP), substantive post-processing requirements and material compatibility were revealed to be barriers in adoption.

The impacts of utilizing AM for procurement of spare parts on the overall resilience of the supply chain were highlighted. Theoretical analysis of the findings was based on theoretical aspects of SCR. This was especially regarding efficient spare parts inventory management. The study results revealed the factors responsible adoption of the AM technology. A novel approach was undertaken to study the effect of AM adoption on “time-to-market” of newly launched products.

The research provided insights regarding practical applications of AM adoption in spare parts procurement. The study could be beneficial to the early adopters of AM across industries for making managerial decisions. Unfamiliarity of supply chain managers with the AM technology was believed to be a major reason to adopt the technology. The study provided essential inputs regarding challenges and alternate adoption strategies of AM. Thus, the research was believed to be of potential value for creating awareness among supply chain managers regarding AM technology.

The research provided new insights on the impact of AM adoption in the context of SCR toward efficient spare parts inventory management. Various limiting and facilitating factors specific to Indian context were also explored.

This paper explores the orchestration of digital innovation in Industry 4.0 organisations.

The study applies the activity theory to explorative multiple case studies. Observations of innovation activities in five business cases take place at two large international organisations.

The results underline five logics of action that drive digital innovation: (1) digital transformation, (2) technology translation, (3) catalyst agents, (4) digital thread and (5) empowerment. Further, the case study organisations highlight the importance of developing a sustainable culture capable of continuously adopting new technologies, processes and infrastructure that will allow the management of digital innovations.

The study empirically shows the motivations and challenges in orchestrating digital innovation in Industry 4.0 organisations.

Creating visibility in the supply chain (SC) helps in making it resilient. Integrating the SC with Industry 4.0 key enabling technologies creates visibility and sustainability in SCs. It also fosters intelligent decision-making, thereby making a SC smart. However, how Industry 4.0 technologies affect key performance indicators (KPIs) of a resilient SC and may help achieve sustainability is rarely studied.

Sixteen KPIs were identified from the literature review and analyzed using fuzzy analytic hierarchy process (FAHP) using expert opinions. Further, a sensitivity analysis was conducted for the KPIs by varying the weightage of the criteria. Later, KPIs results were analyzed, and (1) how and which Industry 4.0 technology helps improve the KPI? (2) Resilience relationship with sustainability? were discussed.

The analyses show that the time-oriented (TO) is an essential criterion and organizational (OR) is the less important comparatively. Lead time, time to market and risk assessment frequency are the top KPIs that need a focus. Blockchain, Big Data and Cyber-physical systems enhance KPI's value and, in turn, foster economic, environmental and social sustainability of the SC and help in better decision making in terms of smart contracts, better forecasting and enhanced real-time information sharing.

Identification of the KPIs, the impact of Industry 4.0 technologies and the impact on sustainability; this kind of interplay is rarely evident in the literature. Understanding the findings of this research will help managers develop smart systems that may work intelligently to overcome risks associated and enhance sustainability. Academicians can use the findings and conduct future research that can overcome the limitations of this research.

This research aims to aid product development managers to estimate the expected cost associated with the development of cost-intensive physical prototypes considering transitions associated with pertinent states of quality of the prototype and corresponding decision policies under the Markovian setting.

The authors evolve two types of optimization-based mathematical models under both deterministic and randomized policies. Under the deterministic policy, the product development managers take certain decisions such as “Do nothing,” “Overhaul,” or “Replace” corresponding to different quality states of prototype such as “Good as new,” “Functional with minor deterioration,” “Functional with major deterioration” and “Non-functional.” Under the randomized policy, the product development managers ascertain the probability distribution associated with these decisions corresponding to various states of quality. In both types of mathematical models, i.e. related to deterministic and randomized settings, minimization of the expected cost of the prototype remains the objective function.

Employing an illustrative case of the operator cabin from the construction equipment domain, the authors ascertain that randomized policy provides us with better decision interventions such that the expected cost of the prototype remains lower than that associated with the deterministic policy. The authors also ascertain the steady-state probabilities associated with a prototype remaining in a particular quality state. These findings have implications for product development budget, time to market, product quality, etc.

The authors’ work contributes toward the development of optimization-driven mathematical models that can encapsulate the nuances related to the uncertainty of transition of quality states of a prototype, decision policies at each quality state of the prototype while considering such facets for all constituent subsystems of the prototype. As opposed to a typical prescriptive study, their study captures the inherent uncertainties associated with states of quality in the context of prototype testing, etc.

This paper aims to determine new-normal uncertainty considerations stemming from the COVID-19 pandemic to consider within transaction-cost analysis for pharmaceuticals. It also aims to propose new-normal market entry strategies to address the uncertainty as a result of COVID-19's implications and provide for lack of knowledge and information in an uncertain business environment by way of Internet of Things (IoT) ecosystem for pharmaceutical market entry.

In this paper, we focus on the uncertainty facet within transaction-cost analysis consideration and utilise a descriptive three-case study approach taking in Johnson and Johnson (J&J), GlaxoSmithKline (GSK) and Novartis to present an ADO (Antecedent-Decisions-Outcomes) understanding of their usual market entry approach, the approach undertaken during the pandemic and the outcomes thereafter facilitating new-normal uncertainty considerations to factor in. Further with this insight, we develop a conceptual framework addressing the transaction-cost analysis implications of uncertainties toward lack of knowledge and information for a new-normal market entry approach and operating strategy for pharmaceuticals applicable due to IoT (Internet of Things).

Uncertainty (external and internal) is different now in the new-normal business environment for pharmaceuticals and boils down to acute shortage of knowledge and information impact to make an appropriately informed decision. Therefore, considering the changed factors to consider, pharmaceuticals need to be able to undertake market entry with vaccines and medicines by way of IoT thereby enabling, the filling of the gap via real-time data access and sharing, including enhancing predictive analysis for sustenance.

The paper's findings have many theoretical implications highlighted in the manuscript.

The paper's findings have many practical implications highlighted in the manuscript.

This is the first study to our knowledge that throws light on transaction-cost analysis theory's uncertainty facet for pharmaceuticals. It is also the first study that provides a new-normal market entry strategy for pharmaceutical companies built on interoperability of real-time IoT.