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This study aims to suggest directions for innovation-driving paths for sustainable growth through an in-depth case analysis of a successful Internet of Things (IoT) in small- and medium-sized enterprise (SME) in South Korea. IoT is expected to play a significant role in the future industry 4.0 platform. Yet, little is known about how SMEs in the IoT industry (IoT-SMEs hereafter) pursue innovation in alignment with attributes inherent in the IoT.

This study addresses relatively unexplored key research questions on innovation strategies of IoT-SMEs. To do so, we employ an exploratory research methodology, along with an extensive review of the literature in the areas of the IoT, SMEs innovation and sustainable growth strategy. Specifically, we conduct intensive individual interviews to find IoT inherent innovation attributes and a case study to explore the process of linking these attributes to innovation-driving paths.

The analysis results reveal that there exist disruptive and open innovation attributes in the IoT industry that enable IoT-SMEs to enhance their structure and process related capabilities, to create business models for products and services and to collaborate with external parties in marketing to enter the market. We excavate practical insights into driving innovation based on IoT attributes and suggest enabling paths for pursuing innovation and entering overseas markets for IoT-SMEs.

This study investigates an underexplored significant area of research on the relationship between IoT attributes and innovation paths. The findings provide profound theoretical and practical implications. To the best of the author’s knowledge, it is the first attempt to link disruptive and open IoT attributes to innovation paths of IoT-SMEs. The results provide directions for pursuing effective innovation in responding to the IoT market for sustainable growth.

To solve the path planning problem of the intelligent driving vehicular, this paper designs a hybrid path planning algorithm based on optimized reinforcement learning (RL) and improved particle swarm optimization (PSO).

First, the authors optimized the hyper-parameters of RL to make it converge quickly and learn more efficiently. Then the authors designed a pre-set operation for PSO to reduce the calculation of invalid particles. Finally, the authors proposed a correction variable that can be obtained from the cumulative reward of RL; this revises the fitness of the individual optimal particle and global optimal position of PSO to achieve an efficient path planning result. The authors also designed a selection parameter system to help to select the optimal path.

Simulation analysis and experimental test results proved that the proposed algorithm has advantages in terms of practicability and efficiency. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The authors designed a pre-set operation to reduce the participation of invalid particles in the calculation in PSO. And then, the authors designed a method to optimize hyper-parameters to improve learning efficiency of RL. And then they used RL trained PSO to plan path. The authors also proposed an optimal path evaluation system. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The purpose of this paper is to demonstrate System-of-Systems (SoS) approach to design and development of unmanned robotic platform for greenhouse agricultural application.

SoS design approach is important in developing engineering products. It was observed that while system integration considers designs in a multi-disciplinary level framework, SoS is viewed as a solution focussed approach. In this paper, the authors have demonstrated SoS approach to develop a mobile robot platform. The wheels of the platform are independently controlled by using brushless DC and stepper motors based on fieldbus type Distributed Control System scheme.

The constraints for autonomous traveling were identified during the first phase followed by development of 12 distinct sub-routines during second phase of training. Optimal camera installation angle, driving speeds, steering angle per pixel were found to be valuable constraints for feed-forward parameters for real-time driving. The platform was field tested in a tomato planted greenhouse for yield and weed mapping.

The paper focusses on studying vision-based autonomous four-wheel-drive (4WD) constraints and their implementation limitations.

The platform was field tested in a tomato planted greenhouse for yield and weed mapping.

The platform can be used for agricultural operations such as crop scouting, monitoring, spraying, and mapping in a medium to large-scale greenhouse setting.

The research and presentation is original. Starting from its mechanical specification to wheel performance study, development of path patterns for training and global navigation algorithm for testing and validation were achieved. The platform can autonomously be driven without any manual intervention.

This study elicits the critical attributes, consequences and values associated with the purchasing process in the context of cross-border e-commerce (CBEC). The purpose is to provide a better understanding of the fundamental factors that determine consumer values in CBEC.

The study applies the means-end-chain theory and soft-laddering techniques to interview 60 CBEC consumers to construct an implication matrix and a hierarchical value map (HVM) of the consumer purchasing process, consisting of attribute-consequence-value (A-C-V) paths.

By analyzing the significant linkages, elements, ladders and chains in the HVM, four dominant A-C-V paths were identified: economic-driven, efficiency-driven, progress-driven and quality-driven paths.

This study included only Chinese CBEC buyers. This limitation might affect the generalizability of the conclusions as culture, purchase habits and economic development differ between China and other countries.

The results of this study provide CBEC practitioners an understanding of the consumer purchasing process and how consumer values are associated with platform characteristics. Thus, the results aid practitioners in allocating resources and developing CBEC platforms in an appropriate manner and direction.

This study sheds lights on the emerging phenomenon of CBEC. By applying the means-end-chain approach, the study provides a comprehensive HVM for interpreting the consumer online purchasing process in this novel context. By illustrating the dominant paths, this research provides deeper theoretical insights into the specific focuses of CBEC consumer purchasing.

The purpose of this paper is to present a mobile robot with an olfactory capability for hazardous site survey. Possible applications include detection of gas leaks and dangerous substances along predefined paths, inspection of pipes in factories, and mine sweeping.

The mobile sentry is equipped with a transducer array of tin oxide chemical sensors, compliant with the standard interface IEEE 1451, which provides odour‐sensing capability, and uses differential drive and spring‐suspended odometric trackballs to move and localize in the environment. The monitoring strategy comprises two stages. First, a path learning operation is performed where the vehicle is remotely controlled through some potential critical locations of the environment, such as valves, pressure vessels, and pipelines. Then, the robot automatically tracks the prerecorded trajectory, while serving as an electronic watch by providing a real‐time olfactory map of the environment. Laboratory experiments are described to validate the approach and assess the performance of the proposed system.

The approach was shown to be effective in experimental trials where the robot was able to detect multiple odour sources and differentiate between sources very close to one another.

One limitation of the methodology is that it has been specifically designed for odour detection along a well‐defined path in a highly structured environment, such as that expected in the industrial field. The problem of detection of leakages outside the search path is not addressed here.

This mobile robot can be of great value to detect hazardous fluid leakages in chemical warehouses and industrial sites, thus increasing the safety level for human operators.

The paper describes a mobile robotic system, which employs an odour‐sensing capability to perform automated monitoring of hazardous industrial sites. A dynamic model of the mobile nose is also discussed and it is shown that it well describes the behaviour of the system.

In the era of big data, data have become an essential factor of production. In the context of open government data (OGD), encouraging the commercial development of OGD is significant for promoting mass innovation and entrepreneurship. This study aims to explore the configurational impact of data supply, external environment and entrepreneurial foundation on data-driven entrepreneurship.

This research used a fuzzy set qualitative comparative analysis (fsQCA). Fourteen start-ups using OGD were taken as a case sample.

This study produces two paths to achieving high entrepreneurial performance, one is a financing-enhanced entrepreneurial path and the other is a data-driven entrepreneurial path. Besides, four conditions are necessary for high performance of OGD-based entrepreneurship: good data quality, mature legal environment, favorable market environment and abundant big data entrepreneurial talents.

The findings have important practical implications for formulating policies related to promoting the application of government open data and innovation and entrepreneurship in terms of strengthening top-level design, improving the legal environment, developing the data market and cultivating entrepreneurial talents.

Although many studies have been conducted on OGD, studies on the paths to successful entrepreneurship based on OGD are limited. In this study, this issue is investigated from a configurational perspective by using the fsQCA technique.

The purpose of this paper is to perform a literature review of peer-reviewed journal articles investigating the relationship between Lean and Green management in light of developing an integrated management model.

After an extensive search, 60 articles from 1996 to 2016 were identified as relevant to this study.

The evidence of successful integration of Lean and Green management has largely been weak. The strongest positive evidence between the two management philosophies has been for Lean implementation pushing Green outcomes through operational waste reduction, thus improving environmental performance. The majority of studies suggest highly optimistic outcomes from integrating Lean and Green, however, an integrated operating model of the firm relating Lean and Green is lacking.

The literature review suggests the necessary elements for proposing an integrated operating model of the firm.

The paper offers interesting implications for managers. While most Lean implementations have resulted in some positive environmental outcomes, both management philosophies tend to be implemented independently. Integrating the implementation of Lean and Green offers the potential for synergistic returns.

The findings are derived from a systematic literature review of articles that have studied the relation between Lean and Green management, resulting in a proposed integrated model of firm performance.

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect the performance of waste classification governance.

Content analysis of the existing waste classification policies is conducted using the Latent Dirichlet Allocation (LDA) model. Based on this analysis, influencing factors are identified through the technology-organization-environment (TOE) research framework. The condition configurations and action paths that cause differences in governance performance are derived using the fuzzy-set qualitative comparative analysis method (fsQCA).

The results show that there are spatial and temporal disparities in waste classification policies among different provinces/cities. In most situations, the implementation effect of policy combinations is better than that of a single type of policy, with mandatory policies playing a key role. Additionally, a single influencing factor cannot constitute the bottleneck of high governance performance. Policy topics coordinate with environmental and technical factors to influence governance performance. Finally, in light of China's actual governance situation, several targeted implications are proposed for the practical optimization of local government waste classification governance.

This paper presents a novel approach by integrating multiple heterogeneous data sources from both online and offline channels, adopting a public-government perspective and applying the fsQCA method to investigate the combined effects of technical, organizational and environmental factors on waste classification governance performance across 31 provinces and cities in China.

This paper aims to propose a method for automatic design of additive manufacturing (AM) flow channel paths driven by path length and pressure loss. The research focuses on the automatic design of channel paths, intending to achieve the shortest flow channel length or minimum pressure loss and improve the design efficiency of AM parts.

The initial layout of the flow channels is redesigned to consider the channels print supports. Boundary conditions and constraints are defined according to the redesigned channels layout, and the equation consisting of channel length and pressure loss is used as the objective function. Then the path planning simulation is performed based on particle swarm algorithm. The proposed method describes the path of flow channels using spline cures. The spline curve is controlled by particle (one particle represents a path), and the particle is randomly generated within the design space. After the path planning simulation is completed, the generated paths are used to create 3D parts.

Case study 1 demonstrates the automatic design of hydraulic spool valve. Compared to conventional spool valve, the pressure loss was reduced by 86% and the mass was reduced by 83%. The design results of case study 2 indicate that this approach is able to find the shortest channel path with lower computational cost.

The automatic design method of flow channel paths driven by path length and pressure loss presented in this paper provides a novel solution for the creation of AM flow components.

Mobile peer‐to‐peer communications is an essential phase in the evolution of mobile communications technologies, motivating this research which aims to focus on how established industry stakeholders and new entrants can adapt themselves to the new situation.

Based on existing literature, the authors identified three distinctive evolution paths for mobile peer‐to‐peer communications and developed an analysis framework for their comparison. The authors validated the analysis by conducting a questionnaire study among domain experts, and analyzed its results using statistical analysis.

Internet‐driven evolution has high value proposition, is profitable and has subscription fees as an important revenue model. Telecom‐driven evolution creates value, leverages markets, leverages competence, is likely to encounter regulatory intervention and benefits all customer segments. Proprietary evolution has a successful revenue model, results in alliances of competitors and is competence‐enhancing to mobile device vendors.

Future work consists mainly of analyzing quantitatively the implications of the new technologies when they become readily available and evaluating the value analysis framework in other applicable cases.

Internet‐driven evolution enables new business opportunities to independent service operators and equipment vendors by enabling opportunities in profiting from sales of advanced devices and networks. Telecom‐driven evolution benefits mostly incumbent mobile network operators. Proprietary evolution enables limited competition against incumbent actors by independent service operators.

This study is one of the first journal publications on mobile peer‐to‐peer communications from a holistic techno‐economic point of view, beneficial to both academics and practitioners.