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The purpose of this paper is to examine the non-linear aspects of the asymmetry-performance relationship under varying conditions of trust and innovation. Its novel approach is useful for addressing the strategic elements of supply chain management (SCM) relationships based on trust and innovation decisions.

Results are based on a study of 90 managers from small- and medium-sized firms in Spain. Instead of a classical linear relationship analysis, the authors performed a non-linear analysis, using polynomial modeling and Warp 3 partial least squares method, which provides a more nuanced view of the data and constitutes an original approach to empirical research in SCM.

This study adds a new viewpoint on SC relationships by suggesting that not all trust and innovation development leads directly to performance improvement. The principal finding is, in varying trust and innovation contexts, that the influences of asymmetry on performance have uneven characteristics and follow non-linear paths.

This study focuses on only one particular institutional environment in one country. The data are also cross-sectional, which makes it difficult to empirically test causality.

The findings provide rational insights to managers on when it is appropriate to reduce (or not) asymmetric relationships with partners.

Trust and innovation are important and ones of the key requirements of supply chain relationships in any environment, this study argues that the interactions of key SCM elements that drive members to better performance are more complex and non-linear.

This article presents a new approach to modeling the relationships of eco-innovation. The impact of eco-innovation on organizational performance is well known, but the opposite direction has not been explored.

The research used an online questionnaire survey emailed to 100 Ecuadorian managers. Data obtained from the 62 respondents were analyzed through structural equation modeling.

The results confirm that while eco-innovation increases company performance, higher performance is negatively related to eco-innovation, with managers preferring to dedicate company resources to projects with more significant benefits and lower outlay.

This study was conducted in one country, so generalizability may be limited. Moreover, the cross-sectional data prevent inferences of causality.

Eco-innovation activities are important to managers and can help them with a new definition of company strategy. The findings confirm that eco-innovation drives performance but not vice versa. It could be necessary to modify the strategy to create a sustainable business.

The results elucidate both directions of the relationship between eco-innovation and performance, representing a new contribution to the literature. The results also confirm that eco-innovation activities are valuable tools in building and developing emerging economies.

Este documento presenta un nuevo enfoque del modelo de la eco-innovación. La relación entre la eco-innovación y el resultado empresarial es bien conocida. Sin embargo, la relación inversa no ha sido investigada con la misma dedicación.

En nuestra investigación utilizamos el método de encuesta electrónica. Se enviaron cuestionarios a 100 gerentes ecuatorianos, recibiendo las 62 respuestas válidas. Los datos obtenidos se analizaron mediante modelos de ecuaciones estructurales.

Los resultados confirman que las eco-innovaciones aumentan el resultado de la empresa. Sin embargo, la relación inversa tiene signo negativo; en este contexto, los directivos prefieren dedicar los recursos de la empresa a diferentes proyectos con mayores beneficios y menor gasto que aquellos centrados en la eco-innovación.

Nuestros resultados completan el análisis de las relaciones entre la eco-innovación y el rendimiento empresarial y representan una nueva contribución a la Academia. Los resultados también confirman que las actividades de eco-innovaciones son herramientas valiosas para construir y desarrollar economías en mercados emergentes.

Este estudio se realizó en un entorno específico de un país, por lo que las generalizaciones son limitadas. Nuestros datos son intersectoriales, lo que dificulta establecer relaciones de causalidad.

Los resultados de las actividades relacionadas con la eco-innovación son importantes para los gerentes y pueden ayudarlos redefinir la estrategia de la empresa. Los resultados confirman que la eco-innovación impulsa el rendimiento y muestra que no existe la misma relación entre el rendimiento y las eco-innovaciones. Se podría sugerir que es necesario modificar su estrategia para crear un negocio sostenible.

The purpose of this paper is to examine the influence of asymmetric environments on collaboration, integration, and performance during supply chain management processes.

The study conducted in the industrial sector of two markets – Spain and Poland – considering disparate behaviors among organizations and their managers. Using data collected from 133 firms and advanced partial least squares regression modeling, a number of direct and moderating effects are hypothesized and tested.

The authors found that existing asymmetry may prevent achievement of optimum equilibrium. Seven of the ten research hypotheses were validated, providing strong support for the significant role that asymmetry can play in managing supply chains (SCs). This result suggests that managers need to consider whether maximum collaboration or integration with SC partners is possible under the strong influence of asymmetry. The findings provide rational insights to SC managers regarding adequate measures to reduce imbalanced relationships and establish equilibrium between partners under varying contexts of collaboration and integration.

This study was conducted in only two countries, so generalizations are limited. Furthermore, there are improvements to be made in sample design to allow for further validation and enhancement of the model and method.

Findings provide rational insights to managers regarding when it is adequate to reduce imbalanced relationships with partners under varying contexts of collaboration and integration.

Collaboration and integration have been well studied in many fields but this research suggests that managers in asymmetric environments must understand that development of strategies based on integration might be impossible to realize.

This paper aims to examine the non-linear aspects of the relationship between asymmetry and performance in supply chains (SCs), under varying intensities of collaboration and integration.

The paper offers a useful new approach to designing strategic elements of supply chain management (SCM) relationships. Using the partial least squares method, an empirical study of 66 companies in Spain has been conducted to clarify contemporary relationships, suggest new directions and ultimately contribute toward developing SCM theory.

The influences of asymmetry on performance in varying collaboration and integration contexts are shown to be unstable and have non-linear paths. It is inappropriate for all firms to collaborate or integrate continually, even for a prescribed period. Furthermore, due to asymmetry, SCM processes are more complex.

The results’ validity may be limited to contexts specific to Spanish SCs. It would be valuable to investigate the impact of asymmetry on firms’ performance and relationships in other markets.

Collaborations and integration between partners in a SC might change the role of asymmetry from restraining to improving performance. The best way to improve performance in asymmetric relationships is to collaborate. Certain dimensions of integration and full integration are not necessarily required to improve firms’ performance under asymmetry conditions.

The study adds a new viewpoint on SCM by suggesting that not all collaboration and integration developments lead directly to improved performance.

This paper aims to determine how the level of logistics service quality facilitates logistics performance in emerging markets. The authors chose Ecuador because it is an emerging economy with relatively stable economic development, making it an attractive research platform in a challenging environment for logistics services. The authors empirically test the influence on performance and one another of five dimensions of service quality: reliability, responsiveness, empathy, assurance and tangibility.

SERVQUAL and partial least squares structural equation modeling was undertaken to test the proposed relationships empirically.

The performance was positively related to assurance, tangibility and reliability but negatively related to the responsiveness and empathy dimensions. The findings suggest the order of priority for improvement actions. The findings highlight that the existing relationships in developed markets do not apply in the same manner in emerging markets.

Although representative, data were only collected in one specific market.

The results reveal a mix of activities that managers should develop to improve the services they provide, relationships with customers and performance.

Few other works have explored logistics service quality in South America's emerging markets. According to contingency theory, various combinations of service quality dimensions can influence performance, suggesting that managers should aim for optimal fit between dimensions according to internal and external situations. An efficient and effective combination in one case may be unsuccessful in another. The approaches presented can improve relationships within global supply chains, especially regarding logistics management.

Real-time location sensing (RTLS) systems offer a significant potential to advance the management of construction processes by potentially providing real-time access to the locations of workers and equipment. Many location-sensing technologies tend to perform poorly for indoor work environments and generate large data sets that are somewhat difficult to process in a meaningful way. Unfortunately, little is still known regarding the practical benefits of converting raw worker tracking data into meaningful information about construction project progress, effectively impeding widespread adoption in construction.

The presented framework is designed to automate as many steps as possible, aiming to avoid manual procedures that significantly increase the time between progress estimation updates. The authors apply simple location tracking sensor data that does not require personal handling, to ensure continuous data acquisition. They use a generic and non-site-specific knowledge base (KB) created through domain expert interviews. The sensor data and KB are analyzed in an abductive reasoning framework implemented in Answer Set Programming (extended to support spatial and temporal reasoning), a logic programming paradigm developed within the artificial intelligence domain.

This work demonstrates how abductive reasoning can be applied to automatically generate rich and qualitative information about activities that have been carried out on a construction site. These activities are subsequently used for reasoning about the progress of the construction project. Our framework delivers an upper bound on project progress (“optimistic estimates”) within a practical amount of time, in the order of seconds. The target user group is construction management by providing project planning decision support.

The KB developed for this early-stage research does not encapsulate an exhaustive body of domain expert knowledge. Instead, it consists of excerpts of activities in the analyzed construction site. The KB is developed to be non-site-specific, but it is not validated as the performed experiments were carried out on one single construction site.

The presented work enables automated processing of simple location tracking sensor data, which provides construction management with detailed insight into construction site progress without performing labor-intensive procedures common nowadays.

While automated progress estimation and activity recognition in construction have been studied for some time, the authors approach it differently. Instead of expensive equipment, manually acquired, information-rich sensor data, the authors apply simple data, domain knowledge and a logical reasoning system for which the results are promising.