The antecedents of digital collaboration through an enhanced digital platform for destination management: A micro-DMO perspective

While the tourism sector shifts towards digital transformation, Destination Management Organisations (DMOs) often struggle to adapt to their changing technological environment. This study explores the antecedents of digital collaboration and develops a framework for micro-DMOs to enhance effective destination management through digital technologies. An integrated sequential qualitative approach was adopted by conducting multi-phase interviews, in addition to designing and trialling a real-world trial digital platform. The research provides empirical evidence that digital collaboration is essential for micro-DMOs, necessitating them to transform their current “websites” into digital platforms which act as a hub for business stakeholders to actively be involved in. Antecedents of successful digital collaboration include mutuality, trust, control, and leadership which may be manifested differently from non-digital collaboration. Additionally, the study identifies three aspects for digital collaboration; marketing, networking and knowledge sharing that demands specific attention. Our results have theoretical, methodological, and practical implications for academia, industry and policymakers.     

技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Conditional Mandates on Management Earnings Forecasts: The Impact on the Cost of Debt

Exploiting a unique conditional disclosure mandate on management earnings forecasts (MEFs) in China, we examine the differential effects of voluntary and mandatory MEFs on the cost of debt. We find that firms providing voluntary MEFs have lower cost of debt than do mandatory forecasters and nonforecasters. The results of the channel analyses reveal that voluntary forecasters have greater commitment to voluntary MEFs in future periods than do mandatory forecasters and nonforecasters, and the precision, accuracy, and timeliness of MEFs are higher for voluntary forecasters than for mandatory forecasters. Additional analyses show that the differential effects of voluntary and mandatory MEFs on cost of debt are stronger for voluntary forecasters operating in opaque information environments, issuing high-quality and confirming forecasts, controlled by private shareholders, and operating in highly competitive product markets. Overall, our results indicate that, compared with mandatory MEFs, voluntary MEFs are more informative for credit investors, particularly for firms facing greater information risk and operating uncertainty.     

预算软约束与风险偏好强化：非均衡式创新中的风险点识别研究

计划经济体制导致资源使用效率低下，社会中存在大量非均衡市场和领域，这为中国企业实施均衡式创新创造了条件。随着均衡式创新的帕累托改进空间逐渐缩小，利用非均衡式创新提升资源使用效率已刻不容缓。在非均衡式创新过程中，政府极易侵入社会主体创新边界，导致创新租值降低或耗散。政府对创新主体的财政资金扶持容易对创新预算形成软约束，导致创新目标替代，强化创新主体的风险偏好，放大创新系统风险，诱发俘获政府行为，最终导致创新企业逆向淘汰。因此，明确政府在创新活动中的边界与风险，对我国实施创新驱动发展战略至关重要。     

Natural resource rents and internal conflicts: Can decentralization lift the curse?

We study how natural resource rents affect the risk of internal conflict within countries and how the federal structure of countries influences this relationship. Natural resource abundance may induce excessive rent-seeking and thus increase the risk of internal conflict. Fiscal and political decentralization as an institutional arrangement for rent-sharing and political codetermination of regions within a country may limit the destructive effect of natural resource rents on internal stability. Using cross-country and panel data from more than 90 countries covering the period 1984–2004, we find evidence that natural resource rents indeed increase the risk of internal conflict, but this relationship is significantly mitigated by political decentralization.     

Endogenous network efficiency,macroeconomy, and competition: Evidence from the Portuguese banking industry

Although performance analysis has become a vital part of the banking industry, research on the efficiency of Portuguese banking remains scarce and focused on discussing rankings to the detriment of unveiling its productive structure relative to its competition. This issue is of utmost importance considering the relevant transformations in the Portuguese economy over the last ten years. In this study, we developed a network productive structure comprising two paradigms (the production and intermediation approaches, respectively) to assess how market competition and other macro-economic variables impact bank efficiency and their feedback effects in Portugal. Unlike previous research, an integrated multi-layer perceptron (MLP)/hidden Markov model (HMM) was used for the first time to unveil endogeneity among banking competition, macro-economic variables, and the efficiency levels of the production and intermediation approaches in banking. The findings illustrate the pattern of interaction among these variables and verify that the production efficiency is the cornerstone of endogeneity in Portuguese banks. Policy makers will find the results helpful.     

‘It’s a Harsh Fact of Life with the RMA’: neo-liberalism and the realities of community sports facility development by the private sector in New Zealand

Despite the importance of facilities as primary sites for delivery of leisure and sport services, there has been a scarcity of academic literature on the provision of community sports facilities and the processes through which they are developed. In particular, this paper provides empirical analysis of leisure facility provision with a focus on practice and experience of policy and planning actors. By employing a case study approach and semi-structured interviews, the study identified a sharp contrast between the discourse of neo-liberalism and the realities of a highly regulated environment for the private sector under a national legislation of New Zealand, namely the Resource Management Act 1991. While both public and private actors recognised benefits of the resource consent process in mitigating the negative environmental impacts and facilitating public input, the findings also revealed its potential impediments to both private and philanthropic developments and their potential resultant benefits to communities and social citizenship due to its costly, restrictive and undifferentiated nature. Consequently, the paper suggests that future research needs to examine empirical evidence of how social citizenship and citizen engagement are enhanced by both public and private sectors through planning and development of community sports facilities and services.     

Banking union: the problem of untried systems

This article explores the problems the EU and the SRB face in trying to implement a credible system for resolving banks without the use of taxpayer funds as a key part of banking union that avoids the doom loop between indebted banks and indebted sovereigns. It finds that without clear examples of how the system works in practice it is very difficult to provide convincing evidence of what will happen given the large number of options for bailing in, the continuing predilection for bailing out in some states and the lack of fiscal backstop for general threats to financial stability.     

The influence of school size,principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle schools

The aim of the paper is to identify which among the aspects that relate to the composition of the student body, school (district) size, management practices and the school principals' own characteristics are associated with the performance of Italian students at grade 8, measured through standardised test scores in reading and mathematics. The analysis makes use of a student-level efficiency model, and several school level variables are included as explanators for efficiency scores. The results show that, especially for reading, the most influential variables relate to the composition of the student body, while the students' performance in mathematics is partly correlated with the management practices adopted by the school principal/head teacher. Schools and schooling can only explain a minor part of the variance in achievement scores, however, and the characteristics of the students themselves play the most significant role.