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This paper aims to investigate how emerging market multinational enterprises (EMNEs) are integrating and expanding into other emerging market host countries, focusing on Chinese mining companies in Peru.

Adopting a qualitative approach, an in-depth analysis of two Chinese state-owned enterprises’ strategies was conducted, building on stakeholder theory and the business ecosystem perspective.

This study reveals a reliance on high-level political lobbying rather than localized engagement strategies. However, findings point to increasing grassroots resistance among local stakeholders, undermining EMNEs’ bargaining power.

This paper argues for a paradigm shift toward inclusive, cooperative “translocal governance” approaches as empowered communities gain voice. Key contributions include advancing theoretical understanding of changing stakeholder relationships and power configurations in emerging countries, underscoring the rising significance of microlevel sociocultural embeddedness for MNE success and highlighting practical imperatives for EMNEs to embark on rapid localization strategies in Latin America. By elucidating multilayered integration realities in Peru, this interdisciplinary study yields contextualized insights and enriches perspective on the conditions and pathways for EMNEs to build sustainability in Global South emerging market environments.

This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs.

The objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible.

Empirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs.

The proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.

Owing to the finite nature of the boundary of the line (BOL), the conventional method, involving the strong matching of single-variety parts with storage locations at the periphery of the line, proves insufficient for mixed-model assembly lines (MMAL). Consequently, this paper aims to introduce a material distribution scheduling problem considering the shared storage area (MDSPSSA). To address the inherent trade-off requirement of achieving both just-in-time efficiency and energy savings, a mathematical model is developed with the bi-objectives of minimizing line-side inventory and energy consumption.

A nondominated and multipopulation multiobjective grasshopper optimization algorithm (NM-MOGOA) is proposed to address the medium-to-large-scale problem associated with MDSPSSA. This algorithm combines elements from the grasshopper optimization algorithm and the nondominated sorting genetic algorithm-II. The multipopulation and coevolutionary strategy, chaotic mapping and two further optimization operators are used to enhance the overall solution quality.

Finally, the algorithm performance is evaluated by comparing NM-MOGOA with multi-objective grey wolf optimizer, multiobjective equilibrium optimizer and multi-objective atomic orbital search. The experimental findings substantiate the efficacy of NM-MOGOA, demonstrating its promise as a robust solution when confronted with the challenges posed by the MDSPSSA in MMALs.

The material distribution system devised in this paper takes into account the establishment of shared material storage areas between adjacent workstations. It permits the undifferentiated storage of various part types in fixed BOL areas. Concurrently, the innovative NM-MOGOA algorithm serves as the core of the system, supporting the formulation of scheduling plans.

In regarding to operational efficiency and safety improvements, multiple tower crane service scheduling problem is one of the main problems related to tower crane operation but receives limited attention. The current work presents an optimization model for scheduling multiple tower cranes' service with overlapping areas while achieving collision-free between cranes.

The cooperative coevolutionary genetic algorithm (CCGA) was proposed to solve this model. Considering the possible types of cross-tasks, through effectively allocating overlapping area tasks to each crane and then prioritizing the assigned tasks for each crane, the makespan of tower cranes was minimized and the crane collision avoidance was achieved by only allowing one crane entering the overlapping area at one time. A case study of the mega project Daxing International Airport has been investigated to evaluate the performance of the proposed algorithm.

The computational results showed that the CCGA algorithm outperforms two compared algorithms in terms of the optimal makespan and the CPU time. Also, the convergence of CCGA was discussed and compared, which was better than that of traditional genetic algorithm (TGA) for small-sized set (50 tasks) and was almost the same as TGA for large-sized sets.

This paper can provide new perspectives on multiple tower crane service sequencing problem. The proposed model and algorithm can be applied directly to enhance the operational efficiency of tower cranes on construction site.

In socio-technical transition theory, resistance by existing technology and regime resistance plays a key role. The resistance is in the form of intentional improvements; eventually, the regime destabilizes and adopts the new technology, referred to as the sailing-ship effect. Researchers used a structural view and examined it as a strategic action and its relationship with new technology (competitive/symbiotic) in non-fast-changing sailing systems. This study uses a microlevel view and examines it in a fast-changing where products/services are developed by integrating existing technology with new product innovations; their success depends on addressing technical/market uncertainty. This study examines the sailing-ship effect in a fast-changing system and contributes to the socio-technical transition theory.

The authors need to examine the phenomena of the sailing-ship effect in its setting, and a case-study method is appropriate. The selected case provided diverse analytic and heuristic perspectives to examine the phenomena; therefore, it was a single case study.

In an IT scenario, the strategic actions decide and realize agility and competitive advantage by formulating appropriate goals with required budgets and coevolutionary changes to resources at product, process and organizational levels, addressing technical/market uncertainty. Moreover, the agility displayed by strategic actions determines the relationship with new technology, which is interspersed. Finally, it provided insights into struggle, navigation and negotiations, forming strategic actions to display the sailing-ship effect.

The study selected a Banking Financial Services and Insurance product of an IT Services company. As start-ups exhibit inherent (emergent) agility, the authors can examine agility as a combination of emergent and strategic actions by selecting a start-up.

The study highlights the strategic actions specific to an IT services company. It developed its product and services by steering clear from IT innovations such as native cloud and continuous deployment. It improved its products/services with necessary organizational changes and achieved the desired agility and competitive advantage. Therefore, organizations devise appropriate strategic actions to combat the sailing-ship effect apart from setting goals and selecting IT innovations.

The study expands the socio-technical transition theory by selecting a fast-changing system. It provided insights into the relationship between existing and new technology and the strategic actions necessary to manage technical and market uncertainty and achieve the desired competitive advantage, or the sailing-ship effect.

Considering the historical evolution of innovation dynamics, and its paradoxical state, and answering Nelson (2008) and Winter (2014), this paper aims to analyze the dynamics of innovation within the context of the Evolutionary Economic Theory. Specifically, this study looks to unravel the moderating influence of university cooperation on the relationship between innovation expenditure and innovation results. This study aims to provide valuable insights and evidence that can inform strategic decision-making for policymakers and businesses striving to foster innovation-driven economic growth in an ever-evolving global landscape.

The quantitative methodology adopted in this study involved harvesting data from the Latin American Innovation Survey (LAIS) database and cleaning it up using Python to ensure data integrity. Subsequently, SPSS, coupled with the PROCESS macro, was employed to conduct moderation analysis. This methodological approach enabled the examination of the intricate interplay between innovation expenditure, university cooperation and innovation outcomes within a large sample of firms, thereby easing a robust exploration of the hypothesis.

The research highlights the moderating role of university cooperation, showing that collaborative partnerships amplify the impact of innovation spending on innovation results, advancing the understanding of the impact of university-business collaborations. Additionally, the results revealed a positive relationship between innovation expenditure and innovation results, underscoring the significance of R&D investments.

This study highlights the role of university-industry collaborations in enhancing innovation investment outcomes in Latin America. It suggests that managers should proactively engage with universities to access advanced research and foster a culture of innovation. These partnerships can significantly boost a firm's competitive edge and innovation success, marking them as crucial in the rapidly evolving economic environment.

The originality of the paper relies on bridging theoretical concepts from the Evolutionary Economic Theory framework with empirical insights of the moderating role of university cooperation. It addresses a theoretical gap, with a new methodology and offers insights into the complex relationship between universities, businesses and innovation in a constantly changing economic environment, making it clearer how these connections can help boost innovation in practical ways.

Pandemics are frequent events, and the impact of each pandemic makes a strong and long-term effect on companies and markets. Given the potential impact of the COVID-19 pandemic, it is important to investigate the crisis from a different perspective to know how companies have sustained growth in markets. The purpose of this paper is to understand how profit-oriented customer-centric companies (small, medium and large) have responded and adapted to COVID-19 crisis, using the complexity theory.

Drawing upon the complexity theory, a humble attempt is made to develop theoretical propositions by conceptualizing companies as complex adaptive systems. The paper examines companies from three dimensions (i.e. internal mechanism, environment and coevolution).

Companies self-organize, emerge into new states and become adaptive to the changing environment. Companies create knowledge to understand the dynamic anatomy and design survival and growth strategies during and post COVID-19 era. Complex adaptive systems perspective provides companies with insights to deal with complex issues raised due to COVID-19 pandemic. They can handle the impact of pandemic efficiently with complex adaptive systems by developing and implementing appropriate strategies post-COVID-19.

The study reveals how companies evolve and emerge into as complex adaptive systems to adapt themselves to the highly dynamic environment, which are uncertain, unpredictable, nonlinear and multifaceted, in the context of COVID-19. Implications for theory and practice of viewing companies as complex adaptive systems and coevolving structures in the COVID-19 context are discussed.

In this study, we investigate how capability in managing intellectual property may be treated as a type of “dynamic capability,” and we seek to understand how, when it is linked to the new technology development capability of a complex technological organization, these two types of dynamic capabilities may coevolve.

We conducted a longitudinal empirical case study of Airbus, incorporating an abductive research methodology that required investigating theory and empirical data concurrently and iteratively. The data, ranging over a period of two decades from 2000 to 2021, was collected from four different sources, including interviews, internal company documents, publicly available information and patent data.

Our main findings are that the capabilities and roles of the Intellectual Property function in Airbus and their interaction with the company's Technology function have indeed influenced the overall innovation strategy of the organization, and that three coevolutionary phases may be identified in the interactive development of the two functions.

Our investigation into how new technology development and intellectual property (IP) management capabilities coevolve within complex technological organizations, exemplified by Airbus, provides significant theoretical and practical implications. Theoretically, it enhances understanding of capability co-development dynamics in complex organizations, particularly in strategic IP management. Practically, it suggests aligning IP strategy with overall corporate objectives and optimizing organizational structures to promote collaboration and efficiency across IP and technology teams. This alignment may foster innovation, maximize the value of intellectual assets and strengthen collaborations, positioning organizations for long-term success in competitive landscapes.

This study makes a fresh contribution to the innovation studies literature by showing how if intellectual property management is treated as a core function of a complex technological organization – rather than simply as a vehicle for protecting new inventions and products after the fact or simply as a constituent part of the organization's legal function – it may contribute proactively to the organization's technological innovation performance. We also address the current gap in the academic literature for a clear understanding of the processes by which different function-specific dynamic capabilities may coevolve in a complex organization operating as part of a dynamic and complex adaptive system.

Given the contradictory findings of standardization/adaptation of marketing strategy in explaining export performance in the extant research, this study aims to examine the contingent effects of managerial ties and born global orientation in the standardized advertising-export performance conceptualization.

The study used two-respondent method in the survey research by a sample of 155 exporting firms operating in the industrial marketing based in Australia and New Zealand and applied hierarchical regression analysis to test the hypotheses.

The findings demonstrate that standardized advertising has a significant effect on export performance and this relationship is positively moderated by business ties. Such effect is particularly enhanced for born global firms (than nonborn global firms). However, political ties negatively influence the impact of standardized advertising on performance and such effect is stronger for born global firms.

A broader perspective of contingent variables should be included to examine the underlying relationship between standardized advertising and export performance in capturing the dynamism in international marketing contexts, such as institutional frameworks or sociocultural environments in host countries.

Standardized advertising is critical for born global firms’ export performance as it can increase efficiency and speed up internationalization processes. Such positive impact of standardized advertising on export performance is further enhanced if born global firms allocate resources to develop strong business ties with host country partners instead of building political ties with host country governments, because smooth business networking can facilitate standardized advertising on industrial marketing, yet justifiable political relations require intricate negotiations that often prolong internationalization progress.

This study incorporates managerial ties and born global orientation as contingent factors in fixing the theoretic interlock between standardization advertising strategy and export firm performance.

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.