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Developing technological capabilities to enhance innovation performance is essential for firms to respond to external changes and competition. Based on the effect of organizational structure on organizational capability development, this study assesses whether a specific R&D organizational structure design can be used to develop different technological capabilities.

Combining organizational theory and the resource-based view as an integrated view, we propose several contrasting hypotheses to show the effects of three general R&D organizational structure designs (centralized, decentralized, and hybrid) on developing exploitative and explorative capabilities. We propose R&D slack as a moderator. 82 Taiwanese listed manufacturing firms were selected. Data on the firms' annual reports and their patent applications to the Taiwan Patent Office from 2005 to 2017 were collected.

Firms’ adoption of centralized and decentralized R&D structures has a significant positive effect on developing exploitative capability and an opposite effect on developing explorative capability. A high or low R&D slack can moderate the impact of R&D organizational structure on non-routine capability development.

This study concludes that R&D organizational structure affects the development of different technological capabilities and that the effect of R&D organizational structure on the development of technological capabilities can be changed under the moderation of R&D slack, which means that the possibility of developing different technological capabilities under the same organizational structure will increase.

The top manager should consider the relationship between R&D structure design and technological capability development to manage the R&D routines to influence the generation of technological capabilities. Also, they must utilize the provision of R&D slack to modulate technological capability development.

This study reexamines the relationship between organizational structure and capability development. It shows that organizational structure can shape unique technological capabilities and that firms may be able to change structural elements through slack resources, enabling ambidexterity or dynamic capability development without organizational change.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

This study aims to investigate whether managerial short-termism affects the expected default probability for a sample of Chinese-listed firms.

To capture default, we utilize the expected default probability measure developed by Bharath and Shumway (2008). Textual analysis and machine learning techniques are used to construct the index of managerial myopia. We conduct ordinary least squares regression and employ a large sample of 33,164 firm-year observations from Chinese A-share listed firms spanning the years 2001–2021 to test our theoretical hypotheses. We further conduct mediation tests, moderating analysis, textual features analysis and analysis of actual default firms. In addition, we employ change regression, entropy-balanced/propensity score/closest assets matching analysis, two-stage least squares regression, two-stage residual intervention method and alternative estimation methods to address endogeneity concerns.

First, there is a positive and statistically significant relationship between managerial myopia and expected default probability. Second, the mediation tests indicate that managerial myopia increases the expected default probability through operational risk and opportunistic agency channels. Third, the cross-sectional tests reveal that the positive association is less pronounced for firms with effective internal control systems, higher audit quality and more financial analyst coverage.

Our study reveals the need for comprehensive early warning mechanisms in the corporate bond market in China, in particular, through enhanced transparency of managerial incentive schemes and more rigorous disclosure requirements regarding short-term managerial decision-making. Furthermore, the findings of our study suggest the necessity of taking an integrated approach in developing regulatory frameworks that enable market intermediaries – including rating agencies, financial analysts and external auditors – to execute their monitoring functions with greater effectiveness.

Prior research has examined the impact of managers’ demographic characteristics on a range of corporate organizational outcomes; however, there have been few studies investigating the influence of managerial myopia on corporate financial risks. This study advances the literature on the determinants of default probability. It contributes to the limited and emerging studies on the role of managerial myopia by being the first to examine the effect of managerial myopia on expected default probability.

Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

Small and medium-sized contractors are critical to micro and macroeconomic performance. These contractors in South Africa have long been confronted with the problem of business failure because of a plethora of factors, including poor productivity. The purpose of this study is to investigate salient issues undermining the productivity of small and medium-sized contractors in South Africa. This study proposes alternative possibilities to engender productivity improvement.

Qualitative data were collected using semi-structured interviews with 15 contractors in Gauteng Province, South Africa. The research data were analysed using content and causal layered analyses.

Challenges to contractors’ productivity were associated with inadequately skilled workers, management competence and political factors. Skills development, construction business and political factors were dominant stakeholders’ perceptions. Metaphors for construction labour productivity are presented and reconstructed as alternative directions for productivity improvement.

Contractors lose a substantial amount of South African Rand to poor productivity. Alternative directions provided in this study can be leveraged to increase profitability in construction organizations, enhance the social well-being of South Africans and ultimately improve the contribution of contractors to the South African economy.

The causal layered analysis (CLA) applied in this study is novel to construction labour productivity research. The four connected layers of CLA, which make a greater depth of inquiry possible, were explored to investigate labour productivity in construction organizations.