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This study aims to investigate how a firm’s sustainable competitive advantage is influenced by the combination of entrepreneurial ecological orientation, digital transformation and dynamic capabilities.

Based on the qualitative comparative analysis method, this study systematically explores the significant key conditions and configuration effects that affect the growth of sustainable competitive advantage. This study uncovers the causal relationship and complex mechanisms underlying the sustainable and unsustainable competitive advantages for new ventures, by examining the grouping effects of the above three factors – entrepreneurial ecological orientation, digital transformation and dynamic capabilities on those advantages.

A single factor fails to constitute a necessary condition for sustainable competitive advantage. Three types of configurations are beneficial to sustainable competitive advantage, namely, flexible and responsive type, dynamically adjusted type and type of opportunity resource integration, whereas four types of configurations lead to the unsustainable competitive advantage of new ventures, namely, type of organizational rigidity, informal entrepreneurial type, information-blocking type and technology-deficient type.

According to this study, adopting an entrepreneurial ecological orientation is a novel strategic move. This study offers an extensive review of three aspects of entrepreneurial ecological orientation, dynamic capacities and digital transformation and their mutually synergistic cascading effects on the sustainable competitive advantage of new ventures. This study investigates how three dimensions interact to achieve sustainable competitive advantage for firms, ultimately contributing to the study of sustainable competitive advantage strategies from an entrepreneurial ecosystem perspective.

The purpose of this paper is to develop a bi-objective optimization framework to select prefabricated construction service composition. An improved algorithm-genetic simulated annealing algorithm (GSA) is employed to demonstrate the application of the framework.

The weighted aggregate multi-dimensional collaborative relationship is used to quantitatively evaluate the synergistic effect. The quality of service is measured using the same method. The research proposed a service combination selection framework of prefabricated construction that comprehensively considers the quality of service and synergistic effect. The framework is demonstrated by using a GSA that can accept poor solutions with a certain probability. Furthermore, GSA is compared with the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to validate the performance.

The results indicated that GSA has the largest optimal fitness value and synergistic effect compared with other algorithms, and the convergence time and convergence iteration of the improved algorithm are generally at a low level.

The contribution of this study is that the proposed framework enables project managers to clarify the interactions of the prefabricated construction process and provides guidance for project collaborative management. In addition, GSA helps to improve the probability of successful collaboration between potential partners, therefore enhancing client satisfaction.

The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection.

This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model.

The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination.

The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.

This study aims to address the issues of limited pipe diameter adaptability and low inspection efficiency of current pipeline inspection robots, a new type of pipeline inspection robot capable of adapting to various pipe diameters was designed.

The diameter-changing mechanism uses a multilink elastic telescopic structure consisting of telescopic rods, connecting rods and wheel frames, driven by a single motor with a helical drive scheme. A geometric model of the position relationships of the hinge points was established based on the two extreme positions of the diameter-changing mechanism.

A pipeline inspection robot was designed using a simple linkage agency, which significantly reduced the weight of the robot and enhanced its adaptive pipe diameter ability. The analysis determined that the robot could accommodate pipe diameters ranging from 332 mm to 438 mm. A static equilibrium equation was established for the robot in the hovering state, and the minimum pressing force of the wheels against the pipe wall was determined to be 36.68 N. After experimental testing, the robots could successfully pass a height of 15 mm, demonstrating the good obstacle capacity of the robot.

This paper explores and proposes a new type of multilink elastic telescopic variable diameter pipeline inspection robot, which has the characteristics of strong adaptability and flexible operation, which makes it more competitive in the field of pipeline inspection robots and has great potential market value.

The robot is characterized by the innovative design of a multilink elastic telescopic structure and the use of a single motor to drive the wheel for spiral motion. On the basis of reducing the weight of the robot, it has good pipeline adaptability, climbing ability and obstacle-crossing ability.

This study aims to drive the induction machine system with a low switching frequency.

An unconventional inverter control strategy – field-oriented predictive control (FOPC) – is presented. The strategy limits current distortion by setting a boundary circle. The voltage vector, which could keep current trajectories in boundary, is selected to obtain a low switching frequency.

A dual simulation step technique is developed to investigate the influence of sampling frequency on current distortion control and switching frequency. Current control distortion can be improved, i.e. reduced, by increasing the sampling frequency; however, the switching frequency will also increase. Such a law is discovered by the dual simulation step technique and finally verified by experiments.

A new predictive control method, FOPC, is derived from the rotor filed coordinate machine model and presented in this paper. FOPC circumvents derivative calculations, and thus avoids high-frequency noise amplification.

In recent years, the airfoil sections with blunt trailing edge (called flatback airfoils) have been proposed for the inboard regions of large wind‐turbine blades because they provide several structural and aerodynamic performance advantages. The purpose of this paper is to optimize the shape of these airfoils for optimal performance using a multi‐objective genetic algorithm.

A multi‐objective genetic algorithm is employed for shape optimization of flatback airfoils to achieve two objectives, namely the generation of maximum lift as well as the maximum lift to drag ratio. The commercially available software FLUENT is employed for calculation of the flow field using the Reynolds‐Averaged Navier‐Stokes (RANS) equations in conjunction with a two‐equation Shear Stress Transport (SST) turbulence model and a three‐equation k‐kl‐ω turbulence model.

It is shown that the multi‐objective genetic algorithm based optimization can generate superior flatback airfoils compared to those obtained by using a single objective genetic algorithm.

The method of employing genetic algorithms for shape optimization of flatback airfoils could be considered as an excellent example for the optimization of other types of wind turbine blades such as DU FX and S series airfoils.

This paper is the first to employ the multi‐objective genetic algorithm for shape optimization of flatback airfoils for wind‐turbine blades to achieve superior performance.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

This paper aims to provide an optimization method of workflow for publishing houses and electronic book (e-book) studies in the field of digital publishing.

Based on the studies of publishing houses in Beijing, the present conversion workflow is illustrated using a functional modeling methodology. Then, the workflow is analyzed using 5W1H (why, who, what, where, when, how) methodology and optimized using ECRSI (eliminate, combine, rearrange, simplify and increase) principles. To validate the optimization effect, the workflow before and after optimization are generated and implemented by the ExtendSim® simulation software.

The simulation results show that under similar circumstances, both quantity and quality of the products are improved after optimization, which indicate that the optimization method is effective.

Electronic PUBlication (EPUB) has significant requirements to satisfy the needs of the mobile reading market and to earn increased profits, whereas some e-books are still preserved in a portable document format (PDF). This study results in the enhanced EPUB quality and production efficiency of the PDF-to-EPUB format conversion workflow in publishing houses. Publishing houses around the world can refer to this study to make a similar optimization when handling PDF-to-EPUB.

This research introduces the traditional industrial engineering analytical techniques to the workflow optimization of e-book conversion. Compared with the most of other methods used to optimize workflow, this method is simpler, more efficient and more suitable for e-book format conversion.

As one of the United Nations Educational, Scientific and Cultural Organization initiatives, the creative cities network (CCN) declares the cities that are creative in the contexts of music, gastronomy, design, etc., with the aim of promoting cooperation amongst the member cities and maintaining sustainable urban development. This study aims to identify the destination food image of Gaziantep in Turkey, which is a member gastronomy city of the CCN since 2015. Identified destination food image elements were connected to the common targets of the CCN to show how the city may contribute to the network objectives.

A two-stage research process was used in the study. First, qualitative approach was adopted for the clarification of projected and perceived destination food image elements. Projected image elements were derived from a content analysis performed on a totally 113 official, semi-official and unofficial online documents in Turkish and English. Perceived destination food image elements were identified by face-to-face interviews, conducted on 10 participants. As a result, 18 projected and 20 perceived destination food image elements were obtained. These were then grouped under 4 main and 22 sub-categories. At the second stage, destination food image elements were matched with common targets of the CCN.

Destination food image elements, obtained by two qualitative studies, are grouped under 4 main and 22 sub-categories as follows: gastronomic identity (with sub-categories of destination’s identity and local culinary culture); diversity of the destination (with sub-categories of attractiveness of the local food, ease of promotion and high brand value); gastronomic attractions (with sub-categories of restaurants and cafes, culinary museums, farmer markets, orchards, gastronomy tours, gastronomy events (e.g. festivals, competitions), culinary education, books on gastronomy, certification systems, organizations, street foods and vendors and handmade or homemade foods); and qualified workforce and stakeholders (with sub-categories of expert chefs and cooks, specialist suppliers, service personnel, locals and local authorities). These are then connected to the common CCN targets (e.g. cuisine, tourism and festivals; extension of the creative value chain; fostering cultural creativity; and sustainability).

This is one of the early research attempts in examining a member gastronomy city’s food image elements and the role that they played in the success of the CCN’s common targets. Moreover, the study contributes to the literature on the identification of (projected and perceived) destination food image by using content analysis.

This paper aims to document the adaptation strategies developed by local farmers to adjust to climate change and related hazards in Lijiang Prefecture in Southwest China, and quantify the determinants of the adaptation measures.

The study conducted a household survey with 433 respondents in Lijiang to documents adaptation measures. The authors used a multivariate probit model to quantify five categories of adaptation measures against a set of household features, extension and information, resources, social network, financial assets and perception variables.

The most significant determinants consisted of information on early climate warnings and impending hazards, ownership to land and livestock, irrigation membership in community-based organisations, household savings, cash crop farming and perceptions of climate change and its related hazards. Adaptation strategies and policies highlighting these determinants could help to improve climate change adaptation in the region.

This study quantified the determinants of adaptive strategies and mapped important determinants for the region that will provide farmers with the appropriate resources and information to implement the best practices for adapting to climatic changes. The method and findings could be useful and easily replicable for future agriculture policies.