Search results

Effective and flexible organizational models have become an avenue for driving smallholder competitiveness in the agricultural sector. However, little is understood about the processes by which resource-constrained actors deploy their organizational networks to generate and retain value in rapidly changing agrifood environments. This study examines the moderating effects of business contingencies on the interplay between organizational relationships and the resource-based performance of small-scale farmers in a developing country.

The authors propose a novel conceptual framework grounded in the relational view, netchain and contingency theories. Cross-sectional data obtained from 330 maize farmers in rural Zambia were analyzed using variance-based structural equation modeling, which involves mediation-moderation analysis.

The results show that all relational networks – vertical, horizontal and lateral – positively mediate the effects farm resources and social capital have on farmers' performance. However, these effects change depending on the predominant agency situations. Specifically, asymmetric power from customers and reputable competitors weakens the positive effect of closer horizontal relationships on business performance, while the positive effect of tighter informal vertical relationships on farmers' performance weakens under conditions of high affective trust. Moreover, the gender-based multigroup analyses highlight variations in the contingent relational view of men- and women-headed households.

The study relies on cross-sectional data from one agribusiness sector in Zambia, thus generalizations should be cautious.

The uniqueness of this study lies in the proposed theoretical framework and new empirical insights, which extend the scope of the relational view to small-scale farming households in developing countries.

Various barriers discourage small and medium-sized enterprises (SMEs) from entering or expanding their export activities in the international markets, especially SMEs in emerging markets. The purpose of this study is to look at capacity building to accelerate SMEs’ export performance.

This study draws on contingency theory and takes a resource-based and market-based view to provide a holistic understanding of the issue. This study uses primary data collected via extensive surveys from active SMEs in three main industrial regions in Vietnam to undertake confirmatory factor analysis and structural equation modeling for quantitative analysis.

The results confirm and show the significant effects of various determinants on firms’ export performance. These research findings have scientific contribution and significant implications by understanding the effective internal and external export drivers and mediators in an emerging market and enhancing SMEs’ export performance.

This study helps SMEs to improve their export performance by systemizing their decision-making in export activities, improving main export drivers highlighted in this study and developing required training programs for their teams. The outcomes also helps policymakers and regulators to improve the current SME ecosystem in Vietnam through training programs, improving policies, facilitating trades, providing more government assistance etc. The results of this study can be extended to other emerging markets with a similar economic structure and legal system.

Given the need for more work on export performance, this paper develops and tests a holistic conceptual framework that accounts for all aspects of export drivers, and provides a more comprehensive model for examining SMEs’ export drivers. This theoretical framework also incorporates three potential mediators (i.e. innovation strategy, export marketing strategy and business strategy) to investigate the effect of internal and external factors on export performance, highlighting the importance of the mediating effects on SMEs in achieving growth and competing in the international arena.

Effective planning requires the participation of different functions and may be hampered by lack of integration and information quality (IQ). This paper aims to investigate the relationships among integration, uncertainty, IQ and performance, in the context of the production planning and control function. The literature lacks in-depth studies that consider these factors altogether, showing how they interact and how they contribute to improve business performance.

The authors introduce the variable of planning performance, which represents the quality of the production plans/planning process and is related to the frequency and causes of modifications to these plans. The relationships among the mentioned constructs are investigated by means of multiple case studies.

The results illustrate that integration is positively related to planning performance, and this relationship is mediated by IQ and moderated by uncertainty.

The presented analysis may help practitioners to foster interfunctional integration, better cope with uncertainty and improve information management, aiming to achieve better planning performance. The managers can choose integration and IQ improvement mechanisms that better fit to their environment/reality, using the four different cases as a benchmark. Moreover, this research contributes to the literature exploring this contingency perspective by means of in-depth case studies, considering that most of the existing research adopting this perspective is survey-based.

Artificial intelligence (AI) has started to receive attention in the field of digital entrepreneurship. However, few studies propose AI-based models aimed at assisting entrepreneurs in their day-to-day operations. In addition, extant models from the product design literature, while technically promising, fail to propose methods suitable for opportunity development with high level of uncertainty. This study develops and tests a predictive model that provides entrepreneurs with a digital infrastructure for automated testing. Such an approach aims at harnessing AI-based predictive technologies while keeping the ability to respond to the unexpected.

Based on effectuation theory, this study identifies an AI-based, predictive phase in the “build-measure-learn” loop of Lean startup. The predictive component, based on recommendation algorithm techniques, is integrated into a framework that considers both prediction (causal) and controlled (effectual) logics of action. The performance of the so-called active learning build-measure-predict-learn algorithm is evaluated on a data set collected from a case study.

The results show that the algorithm can predict the desirability level of newly implemented product design decisions (PDDs) in the context of a digital product. The main advantages, in addition to the prediction performance, are the ability to detect cases where predictions are likely to be less precise and an easy-to-assess indicator for product design desirability. The model is found to deal with uncertainty in a threefold way: epistemological expansion through accelerated data gathering, ontological reduction of uncertainty by revealing prior “unknown unknowns” and methodological scaffolding, as the framework accommodates both predictive (causal) and controlled (effectual) practices.

Research about using AI in entrepreneurship is still in a nascent stage. This paper can serve as a starting point for new research on predictive techniques and AI-based infrastructures aiming to support digital entrepreneurs in their day-to-day operations. This work can also encourage theoretical developments, building on effectuation and causation, to better understand Lean startup practices, especially when supported by digital infrastructures accelerating the entrepreneurial process.

Drawing upon the resource-based view and the contingency theory, the purpose of this paper is to build and test a framework of: the interaction between market orientation (MO) and accountants’ participation in strategic decision making; and its subsequent effect on the use of management accounting systems (MASs), which, in turn, enhances firm performance.

The hypotheses were empirically tested using partial least square-structural equation modeling with survey data from 171 large business firms in Vietnam. The standardized root mean squared residual value of the composite model was also examined using SmartPLS3 to test the model fit. The marker-variable technique was employed to test common method bias.

This study has two key findings: first, the use of MAS (in terms of broad scope, timeliness, aggregation, and integration) mediates the effect of MO on firm performance. Second, the degree of accountants’ participation in strategic decision making elevates the positive relationship between MO and the use of MAS.

This study is one of the first empirical attempts to test the contingent roles of accountants’ participation in strategic decision making and the use of MAS information in driving performance of market-oriented firms in the context of a transition market.

This paper aims to develop and argue for a new research path to advance theory on incumbent firm adaptation to discontinuous technological change. Integrating variance and process epistemologies, implications of distinguishing a firm's capacity to adapt from their adaptive choices are highlighted.

The concepts and argument presented are based on an extensive review and synthesis of the literature on the phenomenon.

Distinguishing resource-based capacity variables and behavioral-based choice variables can fuel progress in the literature on incumbent adaptation to technological changes. More attention is needed on the direct, proximate determinants of what occurs in the process of adaptation, e.g. the intermediate choices to adapt, the timing of adaptive actions and the selection of a means for adapting. Work must then associate specific choices with performance outcomes to complete both sides of the mediated cause-effect model connecting characteristics of the decision issue to performance.

Most studies toward understanding how incumbent firms adapt to discontinuous technological innovation have used variance analyses to identify firm and technology characteristics that explain adaptation outcomes. Focusing on characteristics and content, however, does not adequately explain why or how firms adapt. Scholars thus continue to lament the lack of clear, practical theory. I contend one heretofore unaddressed reason for this dissatisfaction is that too much of the research base neglects the importance of understanding choices and the factors affecting them.

A low-carbon economy is the pressing need of the hour. Despite several efforts taken by the government and large corporations, there is still research to be conducted exploring the role of top management commitment in translating external pressures into responses that help to build low-carbon emissions in supply chains.

The authors have grounded their framework in institutional theory, agency theory and contingency theory. On the basis of existing literature, four hypotheses were drawn. To test these hypotheses, a questionnaire was developed and pre-tested. Finally, statistical analyses were performed to test the research hypotheses using 176 samples gathered using a pre-tested questionnaire following Dillman’s (2007) total design test method.

The results suggest that coercive pressures and mimetic pressures under the mediating effect of top management commitment have a significant influence on organizational response to low-carbon emissions. The authors further note that supply base complexity has moderating effects on the link between top management commitment and organizational response towards low-carbon emissions.

This study offers valuable insights to those managers and environmental consultants who view supply base complexity as a limitation. However, the results indicate that supply base complexity may help to enhance the effectiveness of the top management commitment on organizational response towards low-carbon emissions.

Due to its fast growth, cross-border e-commerce (CBEC) is becoming a popular internationalization model, especially in those destination markets with impressive e-commerce development like China. However, CBEC also brings new logistics challenges and uncertainty. This paper aims to understand how companies cope with logistics uncertainty in this field and whether the different types of uncertainty influence the risk management strategies adopted to face them.

A survey targeting online exporters to China and third-party forwarding logistics service providers (3PFLs) is conducted. A structural equation model (SEM) analysis is performed to test the possible relationship between the adopted risk management strategies and the types of uncertainty. The type, industry and size of the company, as well as the distance between the company's home country and China, are used as control variables in the study. Survey results are enriched via interviews with some of the respondents.

The risk management strategies adopted are dependent on the type of logistics uncertainty that the companies face and, to a minor extent, on the industry the company operates in. Conversely, no significant influence is exerted by other types of control factors, i.e. home country, company size or company type.

The paper investigates logistics uncertainty and risk management approaches in the novel context of CBEC. A systematic review of relevant sources of uncertainty is offered to help both scholars and practitioners understand the current complexities of CBEC. From a theoretical perspective, the paper models the investigated concepts in light of the contingency approach. From a practical perspective, results can be of interest since the list of proposed items can support risk identification and evaluation while the interviews with managers can provide insights on risk management practices.

The purpose of this paper is to develop further understanding of the interdependence between product and organization subsystems in the context of major projects by empirically elaborating the volume-variety matrix.

Projects are perceived as systems that include a product subsystem (the project outcome) and an organization subsystem (the temporary multi-firm organizational network that produces the project outcome). This study addresses product-organization interdependence by analyzing product and organization subsystem components in terms of their uniqueness and reuse across multiple projects. The empirical analysis focuses on four global renewable fuels refinery projects implemented by Neste from 2003 to 2011. The refineries are based on the same proprietary technology but are unique at the project level.

The findings indicate interesting interdependencies between product and organization subsystems when analyzed at the component level: the findings suggest both diagonal and off-diagonal positions in the volume-variety matrix. An example of an off-diagonal position is a reused organization subsystem component associated with a unique product subsystem component, meaning that choosing the same organization in a future project can be used for acquiring an improved and, thereby, unique product subsystem component.

The study elaborates upon the volume-variety matrix in the context of major projects. The findings related to off-diagonal positions in the matrix provide new knowledge on combinations at the component level where a reused organization can be associated with a unique product, and vice versa. This has direct implications for management of projects.

Risks can easily disrupt the demand–supply match targeted by sales and operations planning (S&OP). As surprisingly little is known of how organizations identify, assess, treat and monitor risks through tactical planning processes, this paper zooms in on the S&OP set-up and process parameters to explore how risks are managed through S&OP.

A multiple case study analyzes the S&OP processes of seven organizations in the process industry, drawing on 17 in-depth interviews with high-ranking representatives, internal and external documents, and a group meeting with participating organizations.

The study finds that organizations proactively design their S&OP based on their main risk focus stemming from the planning environment. In turn, such designs proactively support organizations' risk identification, assessment, treatment and monitoring through their S&OP execution. Reactively, a crisis S&OP meeting – making use of the structure of S&OP – can be used as a risk-treatment tool, and S&OP design can be temporarily adapted to deal with emerging risks.

This study is among the first to empirically elucidate risk management through S&OP. S&OP design, execution and adaption are identified as three interconnected strategies that allow organizations to manage risks. The design enables risk management activities in the monthly execution of S&OP. The reactive role of S&OP in risk management is particularly novel.