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The paper aims to explain how agility capabilities (competence, flexibility, responsiveness and speed) influence the chance of improving a small and medium-sized enterprise's (SME's) competitive position, measured by market share and profit.

Combining organisational agility with competitiveness, the authors analysed how an SME's activities in the field of agility capabilities – competence, flexibility, responsiveness and speed – influence the chance of improving their competitive position. Data were collected from 1,286 SMEs from Poland using the computer-assisted personal interviews method (CAPI). To analyse the data, the authors used logistic regression and odds ratios.

The study provides empirical evidence of the relationship between agility capabilities and an SME's competitive position. First, the results suggest that all the studied agility capabilities positively impact SMEs' competitive position. Second, the study shows that seeking to increase market share requires particular attention to flexibility, the impact of which is slightly higher than that of the other variables. Third, the findings suggest that the drive to increase profitability requires an appreciation of responsiveness and competence.

The literature contains much discussion about the relationship between agility capabilities and a company's competitive position. However, these studies refer to large companies, whilst the question of the relationship between agility capabilities and competitive position amongst SMEs remains mainly unanswered, which given SMEs' contribution to the creation of economic growth, seems difficult to understand. Although small companies are by nature highly flexible, due to the size of the companies' operations and flattened and decentralised structure, companies' competitive potential is limited as a result of the limited resources that can be devoted to developing procedures for change.

This study examines current dynamics, consolidates current knowledge, elicits trends, identifies and analyzes primary research clusters, offers future directions, and develops an integrated framework for Product Advantage (PA) research.

Using the SCOPUS database, this study applied bibliometric analysis (208 articles) and conducted content analysis on the 35 curated articles selected using a combination of bibliographic coupling and the most cited articles.

This study presents the field’s publication trends, most relevant authors, articles, journals, and knowledge structures. It identifies six primary research themes and four major clusters using the thematic map and bibliographic coupling. Marketing and PA, New Product Development (NPD) and PA, Product Innovation and PA, and New product speed and PA are the main clusters. Finally, this study offers directions for future research and provides an integrated framework for PA research.

By developing an ADO framework of PA, the study offers key insights into how PA shapes product outcomes and identifies key antecedents of PA. Firms must focus on firm factors such as market and technological orientation; product factors, such as development time and pre-announcement proficiency; external factors, such as competition; and environmental factors, such as competitive intensity and technological turbulence. It enables firms to create products with high PA, shaping product outcomes and contributing to their competitive advantage.

This is the first study to conduct a two-stage sequential hybrid review of quality articles on PA. It offers an Antecedents-Decisions-Consequences (ADO) framework based on significant studies and offers cluster-wise directors for future research.

High-tech start-up creation is associated with complex challenges originating from quick transformations in technologies and markets. To raise start-up survival and success chances, founders need to ensure a rapid conversion of a venture idea into a working business. This paper aims to explore how identity-related characteristics of founders influence the speed of the start-up creation process.

For this study, a longitudinal multiple-case-study design was selected to identify a vivid flow of decisions and actions taken by high-tech start-ups for analysis in depth. Over 20 months, a series of interviews were organized with founders of six start-ups located in the same business incubator in Russia. Also, a set of additional data sources was engaged, including publicly available data and internal documents provided by businesses.

The findings reveal contrasting dynamics of start-up creation processes among founders with differing role identities. Identity fit and identity misfit are suggested to be serious pull and push factors in the process of organizational becoming through the impact they have on the situational regulatory focus of founders.

The current research contributes to the entrepreneurship stream of research by extending the knowledge of how cognition affects the process of new venture creation.

Based on recent government reports, the manufacturing industry is considered one of the most important sectors in Palestine. In this sense, this empirical study aims to investigate the influence of production performance on financial and market performances, assess the influence of market performance on financial performance and test the mediating role of market performance on the relationship between production and financial performances.

A convenience sampling method was applied. Accordingly, a set of questionnaires was distributed to 384 managers at Palestinian manufacturing enterprises. Structural equation modelling (SEM) was applied to analyse the collected data.

The study findings unveiled that production performance directly positively has a positive and direct influence on the financial and market performances. Furthermore, the result revealed that financial performance is positively affected by market performance level, whereas market performance has a partial mediation role in the relationship between financial and production performances.

The study designs are restricted to the manufacturing companies. Hence, the empirical results may not generalise to the other industries.

The findings of this study can draw responsible parties and firms’ top management attention in developing countries to the importance of market performance as a key pillar of firm performance.

To the best of authors’ knowledge, most of the prior contemporary studies have been restricted to examine the direct relationship and have not considered the mediating influence of market performance. Besides, this study emphasised the inter-relationships between the firms’ performance dimensions. This study contributes to manufacturing firms’ performance literature by providing further validation of the performance scales from a developing countries “Palestine” with unique business environment because it is under ongoing occupation.

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.

This study aims to explore how an organization’s ethical climate determines the type and effectiveness of entrepreneurial marketing activities. Also, this study seeks to identify the most critical intra-organizational capabilities related to entrepreneurial marketing components and explain their role in the path of ethical climate to entrepreneurial marketing, which means moving from the intra- to the extra-organizational environment.

Data were collected from managers working in 100 scientific and research companies in Iran through survey questionnaires. Latent variable structural equation modeling was used to test the hypothesized relationships.

The findings reveal that the linkage between the ethical climate of the organization and entrepreneurial marketing is partially mediated by work engagement. In addition, the mediating role of knowledge transfer was not confirmed. These results imply that the ethical climate of the organization fosters entrepreneurial marketing by enabling employees with absorption, vigor and dedication.

Scientific and research companies in this research are different in size, resources, knowledge management system, organizational structure and products offered to the market; they have different emphasis on innovation and entrepreneurship as well. This issue increases the variety of data and the ability to generalize the results. Still, on the other hand, it reduces the ability to categorize data and increases the amount of outlier data. Future research in a comparative manner between different industries is needed.

This study indicates that an organization’s ethical climate can be a critical predictor of its entrepreneurial marketing as well as effective knowledge transfer and work engagement. In this regard, organizations should pay attention to employee’s perception of the organization’s ethical climate and create an environment that supports productive behaviors, commitment, trust, communication, work dedication, etc., to facilitate knowledge transfer effectively so that the organization can identify market opportunities and turn it into customer-oriented innovation, cocreate value for their customers and increase market share.

In turbulent markets, companies need to introduce quality and reliable products. Still, because the life cycle of products has shortened and the speed of introducing new products has increased, the supply of products will fail if companies are not equipped with new marketing methods. In this regard, the current research will seek to provide a mechanism for organizational capabilities on the road to entrepreneurial marketing by expressing entrepreneurial marketing as an innovative approach and trying to identify factors affecting it.

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.