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How does the interaction between time and knowledge affect the evolution of organizations? Past research in organizational evolution has mostly investigated time and knowledge as two separate variables. In contrast, theoretical perspectives integrating these variables are still seemingly scant. The authors believe that filling this literature gap needs attention. Thus, this study aims to contribute by developing a conceptual framework.

This is a conceptual study. The framework is centred on the concept of “co-evolutionary time”, which the authors explain through a business example from the tourism industry. Supported by a narrative-based style, from a methodological point of view the framework is featured by the attempt to synthesize specific, extant literature into new theoretical development.

As its main theoretical contribution, the co-evolutionary time suggests how firms can adapt in a way that, from an evolutionary perspective, proves fitting both in terms of contents and methods, thus opening possibilities for new long-term social construction and reconstruction. As its main practical contribution, co-evolutionary time can constitute not only a temporary source of organizational success and competitive advantage but also an agent of enduring change and long-term business survival.

As its main novelty, the framework is developed through merging two literature streams. In particular, the authors first consider the literature about time, with a focus on its objective and subjective dimensions. The authors then consider the literature about organizational evolution, with a focus on the co-evolutionary nature of the firm/environment relationship.

This paper aims to develop a method based on artificial intelligence capable of predicting the due date (DD) of job shops in real-time, aiming to assist in the decision-making process of industries.

This paper chooses to use the methodological approach Design Science Research (DSR). The DSR aims to build solutions based on technology to solve relevant issues, where its research results from precise methods in the evaluation and construction of the model. The steps of the DSR are identification of the problem and motivation, definition of the solution’s objectives, design and development, demonstration, evaluation of the solution and the communication of results.

Along with this work, it is possible to verify that the proposed method allows greater accuracy in the DD definition forecasts when compared to conventional calculations.

Some limitations of this study can be pointed. It is possible to mention questions related to the tasks to be informed by users, as they could lead to problems in the performance of the artifact as the input data may not be correctly posted due to the misunderstanding of the question by part of the users.

The proposed artifact is a method capable of contributing to the development of the manufacturing industry to improve the forecast of manufacturing dates, assisting in making decisions related to production planning. The use of real production data contributed to creating, demonstrating and evaluating the artifact. This approach was important for developing the method allowing more reliability.

The criticality of late deliveries in transportation lies in the threat of considerable multi-level supply chain costs. This study aims to reveal the dynamic capabilities playing a facilitating role in preventing delay, thus providing timely delivery, as well as developing an understanding of how and when those capabilities are activated within the supply chain network.

An exploratory study was conducted involving 16 semi-structured expert interviews with the representatives of logistics service providers and shippers. Following an interpretive phenomenology framework, the prevention phenomenon was explained.

Findings revealed two preventive capability categories in delay prevention: (1) proactive capabilities, referring to the enabling actions planned before departure, and (2) reactive capabilities, referring to actions planned after departure. Findings pinpoint that, in addition to the proactive capabilities, reactive capabilities enabled by innovative problem-solving actions are crucial for adapting to a dynamically changing environment in prevention. Moreover, this study shows that prevention capabilities are characterized by tangible and intangible resources and integration of resources with external links which constitute a delay prevention network within a wider service ecosystem.

This study stands out with its specific focus on delay prevention capabilities and enabling actions from the perspectives of logistics service providers and shippers. The premises of the resource-based view are combined with dynamic capabilities theory, leading to a proposed time-based taxonomy of proactive and reactive capabilities in supply chains, aimed at creating value and strengthening resilience.

This study aims to investigate the mediating effect of innovation on the relationship between KM (KM) capabilities and organisational performance in the context of construction firms operating in Pakistan. Worldwide innovation predicts the performance of any firm. Today, the construction industry in Pakistan is booming, which reinforces the need for a study on innovation and KM in this sector.

This empirical study uses a correlational research design. An online survey questionnaire was used as a data collection method. Through convenient sampling, the sample comprised 277 employees from different construction firms working under the Defence Housing Authority (a construction company operating in major cities) in Pakistan. Data were analysed through partial least squares-structural equation modelling (Smart PLS-SEM version 3) to assess the hypothesis.

Data analysis reveals that KM dimensions, knowledge acquisition, application and protection positively and significantly influence organisational performance; however, knowledge conversion is insignificant. Furthermore, innovation positively and substantially mediates the relationship between knowledge acquisition, application, protection, organisational performance and the insignificant terms of knowledge conversion.

This study is limited to the construction industry, and future research should be conducted on larger scales for better generalisation. Other mediators between KM and organisational performance (i.e. organisational complexity, workplace environment, employee knowledge-sharing attitude) should be investigated.

These results are crucial and encourage managers in the construction industry, especially from a developing country like Pakistan, to understand the importance of innovation, the application of KM and the essential role it has in boosting business performance.

This research contributes to the scholarly debate on the mediating role of innovation in the relationship between KM and organisational performance. It also expands the literature on KM through an empirical investigation on the innovation of the construction industry in Pakistan from a management perspective.

This paper aims to identify factors that influence customers' panic buying behavior during the COVID-19 pandemic.

A self-administered questionnaire was distributed to 357 participants in Fiji, and structural equation modeling to analyze the collected data.

Results indicate that expected personal outcomes is positively associated with customers' attitudes while expected community-related outcomes negatively impact customers' attitudes. Factors such as attitude, subjective norms, scarcity, time pressure and perceived competition were found to positively influence customers' panic buying intention. Furthermore, scarcity and time pressure were confirmed to positively influence perceived competitiveness while perceived social detection risk negatively influences customer's panic buying intention.

The findings highlight the need for better measures to ensure that every customer has access to goods and services and is not deprived of such necessities in times of a crisis. These results will assist store managers and policymakers in introducing better management, social policies and resource utilization mechanisms to mitigate panic buying during the pandemic.

This study's findings contribute to the literature on customer's panic buying behavior during a global pandemic. Research in this area remain scarce, inconsistent and inconclusive. Novel insights are generated as this study is the first to combine the theory of planned behavior, privacy calculus theory and protection motivation theory. Applying these theories allows new relationships to be tested to better understand customer behavior during a global pandemic. With most studies on customer behavior during crises and disasters in developed countries, this study generates new insights by exploring customer behavior in a developing country.

Today the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.

In this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).

Further, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.

For lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.

This paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

This paper investigates the strategic behavior of algorithmic trading firms from an innovation economics perspective. The authors seek to uncover the sources of competitive advantage these firms develop to make markets inefficient for them and enable their survival.

First, the authors review expected capability, a quantitative behavioral model of the sustainable, or reliable, profits that lead to survival. Second, they present qualitative data gathered from semi-structured interviews with industry professionals as well as from the academic and industry literatures. They categorize this data into first-order concepts and themes of opportunity-, advantage- and meta-seeking behaviors. Associating the observed sources of competitive advantages with the components of the expected capability model allows us to describe the economic rationale these firms have for developing those sources and explain how they survive.

The data reveals ten sources of competitive advantages, which the authors label according to known ones in the strategic management literature. We find that, due to the dynamically complex environments and their bounded resources, these firms seek heuristic compromise among these ten, which leads to satisficing. Their application of innovation methodology that prescribes iterative ex post hypothesis testing appears to quell internal conflict among groups and promote organizational survival. The authors believe their results shed light on the behavior and motivations of algorithmic market actors, but also of innovative firms more generally.

Based upon their review of the literature, this is the first paper to provide such a complete explanation of the strategic behavior of algorithmic trading firms.

The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders’ thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.

The authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.

This study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated “Lead time” as the most crucial, “Product Range” as the second and “Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.

The present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders’ decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.

The present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.

Endeavoring to expand their global market presence, firms often launch products into emerging markets where managers face the daunting task of deploying products by managing available, and often limited, supply chain resources. Yet, literature has not empirically examined managerial resource orchestration in this context. Accordingly, by embedding resource orchestration theory (ROT) into the emerging market context, the authors offer middle-range theorizing on supply chain resource orchestration (SCRO) and empirically test how acquiring, bundling and leveraging activities impact new product launch performance.

The authors test the model by analyzing empirical data from 175 individual product launches into emerging markets using a survey methodology.

The authors’ results suggest that SCRO holds the promise of being a viable middle-range theory in the supply chain field, especially where managers face limited resources and must “work with what they have to do what they can.”

The authors’ study also has some limitations. First, because a panel data service company was used to collect the data, the authors were not provided with any information regarding the respondents' company names or other identifying data. Second, because the authors did not directly interact with the respondents nor were the authors able to contact multiple individuals from their respective organizations, the study was limited to a single-respondent design. However, to counter issues associated with single-response bias, the central constructs in the study referenced phenomena related to a specific product launch project as opposed to constructs at the firm or inter-firm relational level.

The authors’ results reveal that SCRO activities can enhance the performance of new product launches, even in resource-starved emerging market contexts.

The results validate measures for several of the SCRO processes (i.e. supply chain resource acquisition, supply chain resource bundling and supply chain leveraging) and provide evidence that supply chain resource bundling and supply chain leveraging mediate the relationship between supply chain resource acquisition and product launch performance. Further, soft logistics infrastructure is found to be an important boundary condition for these relationships.