Asia Pacific Management Review最新文献

Integrating technical indicators, chip factors and stock news for enhanced stock price predictions: A multi-kernel approach 整合技术指标、筹码因素和股票新闻，提高股价预测能力：多核方法

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.10.001

In the field of stock price forecasting, we are actively seeking to integrate various information to more accurately grasp market dynamics. Although historical stock prices and financial news have been widely used in previous studies, it is relatively rare to find research considering news-based, technical, and chip factors simultaneously and evaluating their combined effect. In this study, we innovatively propose a multi-kernel model that not only combines news-based, technical, and chip factor analysis but also utilizes market data provided by the Taiwan Stock Exchange, including institutional trading situations and stock price technical indicators. The aim is to further enhance the prediction accuracy of stock price dynamics. Based on the frequency of word occurrences, we design a new discriminant index to extract features highly correlated with stock prices from financial news. The empirical results show that our multi-kernel model significantly surpasses the single-kernel model in prediction accuracy. However, we also find that although financial news is somewhat correlated with stock price dynamics, information such as chip factors and stock price technical indicators contribute more significantly in our model. This further validates that our multi-kernel learning algorithm can effectively handle multifaceted data sources and give appropriate weights according to the importance of each data point, thereby enhancing the comprehensiveness of prediction. Through this research, we hope to bring new perspectives and inspirations to the field of stock price forecasting.

在股价预测领域，我们正积极寻求整合各种信息，以更准确地把握市场动态。虽然历史股价和财经新闻已被广泛应用于以往的研究中，但同时考虑新闻因素、技术因素和筹码因素并评估其综合效应的研究却相对较少。在本研究中，我们创新性地提出了一个多核模型，该模型不仅结合了新闻因素、技术因素和筹码因素分析，还利用了台湾证券交易所提供的市场数据，包括机构交易情况和股价技术指标。目的是进一步提高股价动态预测的准确性。基于词的出现频率，我们设计了一种新的判别指标，从财经新闻中提取与股价高度相关的特征。实证结果表明，我们的多核模型在预测准确性上明显优于单核模型。不过，我们也发现，虽然财经新闻与股价动态有一定的相关性，但筹码因素和股价技术指标等信息对我们的模型贡献更大。这进一步验证了我们的多核学习算法可以有效地处理多方面的数据源，并根据每个数据点的重要性给予适当的权重，从而提高预测的全面性。通过这项研究，我们希望能为股价预测领域带来新的视角和启发。

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引用次数: 0

Using a smart contract for the floral supply chain 在花卉供应链中使用智能合约

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.12.004

The floral supply chain is one of the most delicate logistics networks in existence, requiring intensive monitoring of temperature, humidity, and product conditions to ensure the quality of flowers. However, the traditional centralized supply chain involves exchanging information back and forth, and therefore wastes time, money, and resources. In addition, centralized data control without security verification exposes logistics information to the risk of hacking, information tampering, and counterfeiting.

Blockchain technology offers decentralization, immutability, and encryption security. Furthermore, application of Internet of Things (IoT) technology has made it easier to monitor goods and the distribution process. Combining the above two new technologies can effectively improve the transparency and traceability of the floral supply chain and make transactions more secure through the digital signature verification process. In this research, we propose a smart contract for the floral supply chain. Through contract compilation, the proposed contract defines the delivery process status, delivery specifications, and other conditions in the shipping process so that the status of the goods is updated on the blockchain, giving the supply chain higher traceability. This study also defines the process for and conditions of money transactions between buyers and sellers using such smart contracts, thereby automating the transaction, improving its efficiency, and saving on labor costs and paper waste. This research also compares the proposed smart contract to traditional transaction methods. The pros and cons are thoroughly discussed, offering significant benefit to decision makers.

花卉供应链是现存最精细的物流网络之一，需要对温度、湿度和产品条件进行密集监控，以确保花卉的质量。然而，传统的集中式供应链需要来回交换信息，因此浪费了时间、金钱和资源。此外，没有安全验证的集中式数据控制会使物流信息面临黑客攻击、信息篡改和伪造的风险。此外，物联网（IoT）技术的应用使监控货物和配送过程变得更加容易。结合上述两种新技术，可以有效提高花卉供应链的透明度和可追溯性，并通过数字签名验证过程使交易更加安全。在这项研究中，我们提出了一种花卉供应链智能合约。通过合约编制，所提出的合约定义了发货过程中的交货流程状态、交货规格和其他条件，从而在区块链上更新货物状态，使供应链具有更高的可追溯性。本研究还利用此类智能合约定义了买卖双方之间的货币交易流程和条件，从而实现交易自动化，提高交易效率，节省人力成本和纸张浪费。本研究还将拟议的智能合约与传统交易方法进行了比较。对其利弊进行了深入讨论，为决策者提供了重大益处。

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引用次数: 0

FinTech, economic growth, and COVID-19: International evidence 金融科技、经济增长和 COVID-19：国际证据

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.12.006

The growth of financial institutions is typically considered a factor that contributes to economic expansion. Financial institutions’ use of financial technology (FinTech) has resulted in changes in the delivery of financial services, subsequently affecting economic growth. However, the pandemic disrupted the demand and supply of goods worldwide, which has had a detrimental impact on the economy. It is worth investigating whether the global economic slump created by the pandemic have a beneficial influence on the national economy because of the introduction of innovative technologies. Using 778 country-year observations from 193 countries between 2018 and 2021, this study examines and finds that the positive impact of FinTech on economic growth is more pronounced during the pandemic. Further analysis shows that this association holds only in countries with high Internet usage, suggesting that the incremental impact of FinTech on economic growth during the pandemic depends on the extent of local Internet usage. Overall, our findings suggest that FinTech plays an important role in reducing the severity of the pandemic’s subsequent economic impact.

金融机构的增长通常被认为是促进经济扩张的一个因素。金融机构对金融科技（FinTech）的使用改变了金融服务的提供方式，进而影响了经济增长。然而，大流行病扰乱了全球商品的供求关系，对经济产生了不利影响。值得研究的是，大流行病造成的全球经济衰退是否会因为创新技术的引入而对国家经济产生有利影响。本研究利用 2018 年至 2021 年期间来自 193 个国家的 778 个国家年观测数据进行研究，发现金融科技对经济增长的积极影响在大流行期间更为明显。进一步分析表明，这种关联仅在互联网使用率高的国家成立，这表明金融科技在大流行期间对经济增长的增量影响取决于当地互联网的使用程度。总之，我们的研究结果表明，金融科技在降低大流行病后续经济影响的严重程度方面发挥着重要作用。

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引用次数: 0

Drivers of customer satisfaction with restaurants during COVID-19. A survey of young adults in Taiwan and Indonesia 新冠肺炎期间顾客对餐馆满意度的驱动因素。台湾与印尼青少年调查

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.08.001

Consumer behavior and preferences regarding restaurant patronage during a pandemic are different than those under ordinary conditions. This research investigates the new drivers of customer satisfaction with restaurants in two different countries, Indonesia and Taiwan, by surveying young adults and analyzing their responses through various structural equation modeling techniques. The severity of the outbreak in each country moderates the intensity of the effects of the determinants of trust, whereas building trust through safety precautions and a safe physical environment becomes the key factor to achieve customer satisfaction. In fact, under extraordinary conditions of lifestyle disruption involving high perceived uncertainty and risk, such as the COVID-19 pandemic, trust assumes the role of mediator in the relationship between customer satisfaction and its drivers.

大流行病期间消费者光顾餐馆的行为和偏好与普通情况下不同。本研究通过对年轻人进行调查，并通过各种结构方程模型技术对他们的回答进行分析，调查了印度尼西亚和台湾这两个不同国家顾客对餐厅满意度的新驱动因素。每个国家疫情的严重程度都会缓和信任决定因素的影响强度，而通过安全防范措施和安全的物质环境建立信任则成为实现顾客满意的关键因素。事实上，在诸如 COVID-19 大流行病等涉及高感知不确定性和高风险的生活方式破坏的特殊条件下，信任在客户满意度及其驱动因素之间的关系中扮演着中介人的角色。

引用次数: 0

Forecasting vault cash with an extreme value long short-term memory network 用极值长短期记忆网络预测金库现金

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.09.001

Effective cash management is key in banking operations and has implications for cost control, customer service, and risk management. As transactions become more diverse, manual forecasting methods have become inadequate for accurate vault cash forecasting, which involves extensive data analysis. To address this challenge, the banking industry has adopted FinTech tools based on big data and deep learning for various client services. These methods are generally accurate but perform poorly in cases with extreme events, for which data are scarce. In this study, we propose a time series prediction model with long short-term memory and an attention mechanism that effectively predicts the presence of extreme values. We applied extreme value theory to define the extreme value loss for extreme situations and use a sliding window to process time series data. The enhanced extreme value loss function in our model yields improved prediction accuracy for time series data.

We evaluated the proposed model against previous methods in evaluation experiments on data from three branches of a commercial bank in Taiwan, where the vault cash data of each exhibited extreme values. The proposed model was highly accurate: it had a lower mean absolute percentage error and higher trend accuracy than competing methods on a majority of time series, and it was also more accurate in predicting extreme values in time series data.

有效的现金管理是银行运营的关键，对成本控制、客户服务和风险管理都有影响。随着交易日益多样化，人工预测方法已不足以准确预测金库现金，因为这涉及大量数据分析。为了应对这一挑战，银行业采用了基于大数据和深度学习的金融科技工具来提供各种客户服务。这些方法一般都很准确，但在极端事件的情况下表现不佳，因为这方面的数据很少。在本研究中，我们提出了一种具有长期短期记忆和注意力机制的时间序列预测模型，它能有效预测极端值的存在。我们应用极值理论来定义极端情况下的极值损失，并使用滑动窗口来处理时间序列数据。我们在台湾一家商业银行三家分行的数据评估实验中，对所提出的模型与之前的方法进行了对比评估，每家分行的金库现金数据都呈现出极端值。所提出的模型具有很高的准确性：与其他方法相比，它在大多数时间序列上的平均绝对百分比误差更低，趋势准确性更高，而且在预测时间序列数据的极端值方面也更加准确。

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引用次数: 0

Corporate ESG performance and intellectual capital: International evidence 企业环境、社会和公司治理绩效与知识资本：国际证据

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.12.003

This study aims to empirically investigate the relationship between a firm's overall (individual) ESG performance and intellectual capital based on data from globally publicly listed firms across 30 countries from 2000 to 2019. We also explore how the Altman Z-score (the total number of patents and trademarks at the national level) moderates the association between firm’ ESG performance and intellectual capital. We use the Panel FGLS (Feasible Generalized Least Squares) approach to examine whether firms with better ESG performance experience a boost in intellectual capital performance. We present two key findings: (1) ESG performance, with its three main pillars, has a significantly strong positive impact on intellectual capital. This suggests that firms should engage in ESG activities as part of their strategy and, to remain ahead of their competitors, must innovate in ways that prevent rivals from copying their business approach. (2) The greater the number of patents and trademarks at the national level and the higher the Altman Z-score, the more significantly positive is the relationship between ESG performance and intellectual capital. The findings of this study contribute to the scant literature on ESG performance and intellectual capital. Firms with strong ESG performance and outstanding achievements in sustainable development have a competitive advantage; therefore, information about firms' strategies for incorporating, generating, transferring and applying intellectual capital can provide stakeholders with a long-term view of the company's future.

本研究旨在基于 2000 年至 2019 年 30 个国家的全球上市企业数据，实证研究企业整体（个体）环境、社会和公司治理绩效与知识资本之间的关系。我们还探讨了 Altman Z-score（国家层面的专利和商标总数）如何调节企业的环境、社会和治理绩效与知识资本之间的关系。我们使用面板 FGLS（可行广义最小二乘法）方法来检验环境、社会和公司治理表现更好的公司是否会提升智力资本表现。我们得出了两个主要结论：（1）ESG 表现及其三大支柱对智力资本有显著的积极影响。这表明，企业应将参与环境、社会和公司治理活动作为其战略的一部分，并且为了保持领先于竞争对手，必须进行创新，以防止竞争对手模仿其经营方式。(2) 国家层面的专利和商标数量越多，Altman Z 分数越高，ESG 表现与智力资本之间的正相关关系就越显著。本研究的结论为有关环境、社会和公司治理绩效与智力资本的稀缺文献做出了贡献。环境、社会和公司治理表现突出且在可持续发展方面取得杰出成就的企业具有竞争优势；因此，有关企业吸纳、生成、转移和应用知识资本战略的信息可为利益相关者提供对企业未来的长期展望。

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引用次数: 0

A long short-term memory model for forecasting housing prices in Taiwan in the post-epidemic era through big data analytics 通过大数据分析预测台湾后疫情时期房价的长短期记忆模型

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.08.002

This study aims to analyse housing prices in Taiwan in the post-epidemic era, identify the crucial factors influencing them, and develop a suitable method for analysing and forecasting them. This study collects relevant data such as Taiwan's housing price index data from 2002 to 2020 to identify the crucial factors affecting Taiwan's housing prices; this is achieved by constructing a regression model, forecasting Taiwan's housing prices through a constructed long short-term memory (LSTM) model that employs big data analytics, and verifying the efficiency of the proposed models through R-square and root mean square error values. The results indicate that the top 10 factors affecting Taiwan's housing prices are mostly related to mortgage interest rates, suggesting that in Taiwan, the effect on housing prices in the post-epidemic era may be non-significant. This study collects data on Taiwan's housing price for the period from the first quarter of 2002 to the fourth quarter of 2020 to construct an LSTM for forecasting Taiwan's housing prices. The results indicate that the proposed LSTM exhibits good fitness, indicating that the model is suitable for analysing and forecasting housing prices. Given that analysing and forecasting quantity is also crucial in housing market analyses and that this study focuses only on predicting housing prices, future research should explore the simultaneous prediction and analysis of both price and quantity.

本研究旨在分析后疫情时代的台湾房价，找出影响房价的关键因素，并制定合适的分析和预测方法。本研究收集了 2002 年至 2020 年台湾住房价格指数数据等相关数据，以确定影响台湾住房价格的关键因素；通过构建回归模型，利用大数据分析构建的长短期记忆（LSTM）模型预测台湾住房价格，并通过 R 平方和均方根误差值验证所提模型的效率。结果表明，影响台湾房价的十大因素大多与房贷利率有关，这表明在台湾，后疫情时代对房价的影响可能并不显著。本研究收集了 2002 年第一季度至 2020 年第四季度的台湾房价数据，构建了预测台湾房价的 LSTM。结果表明，所提出的 LSTM 具有良好的拟合度，表明该模型适用于分析和预测房价。鉴于数量分析和预测在住房市场分析中也至关重要，而本研究仅侧重于预测住房价格，未来的研究应探讨价格和数量的同步预测和分析。

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引用次数: 0

Signals that sharing economy service providers should send out: The case of codementor 共享经济服务提供商应发出的信号：codementor案例

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-09-01 DOI: 10.1016/j.apmrv.2023.12.002

A sharing economy is an economy that enables individuals to share their assets with or provide services to those in need through online platforms. Information asymmetry prevents consumers from effectively choosing the best service provider for their needs. Therefore, service providers should offer high-quality signals to address this problem. Unlike other studies, which have focused on platforms for sharing tangible assets (e.g., houses), in this study, we focused on platforms for sharing intangible assets (e.g., knowledge). Specifically, we adopted signaling theory to develop a research model for determining the internal and external signals that service providers should provide on their platforms to attract customers. Public data were collected from the Codementor platform by using Python web scraping. After rigorous data processing, the data obtained from 612 service providers were analyzed to identify key signals. Four crucial internal signals were identified: availability of follower information, availability of reviews, free trial, and service cost. In addition, two crucial external signals were identified: number of projects accomplished and endorsements from other websites related to mentor performance. Overall, our findings expand the application of signaling theory to intangible asset transactions and enable service providers to identify the essential signals that they should provide on their sharing economy platforms to increase the number of consumers interested in their services.

共享经济是一种使个人能够通过在线平台与有需要的人共享资产或为其提供服务的经济。信息不对称阻碍了消费者根据自身需求有效选择最佳服务提供商。因此，服务提供商应提供高质量的信号来解决这一问题。与其他研究侧重于有形资产（如房屋）共享平台不同，本研究侧重于无形资产（如知识）共享平台。具体而言，我们采用信号理论建立了一个研究模型，以确定服务提供商应在其平台上提供哪些内部和外部信号来吸引客户。我们使用 Python 网络刮擦技术从 Codementor 平台收集公共数据。经过严格的数据处理后，对从 612 家服务提供商处获得的数据进行了分析，以确定关键信号。确定了四个关键的内部信号：是否有追随者信息、是否有评论、免费试用和服务成本。此外，我们还发现了两个关键的外部信号：已完成项目的数量和其他网站对导师表现的认可。总之，我们的研究结果拓展了信号理论在无形资产交易中的应用，使服务提供商能够确定他们应在共享经济平台上提供的基本信号，以增加对其服务感兴趣的消费者数量。

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引用次数: 0

Beneath the Surface: Uncovering the relationship between ego states, organizational commitment, and productivity among Indian bankers 表象之下揭示印度银行家的自我状态、组织承诺和生产力之间的关系

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-06-01 DOI: 10.1016/j.apmrv.2023.12.001

Habeeb Ur Rahiman , Rashmi Kodikal

Banking is a dominant player among the service providers in India. Interpersonal skills play a vital role in the banking industry, as intangible variables are influenced by communication. Through Transactional Analysis (TA), bankers can render better services to their customers by ensuring that the communication occurs at an acceptable level of ego state. This manuscript sets out to uncover the role of TA in determining the commitment and productivity of bankers. When we delve deeper into the workings of the banks, it is understandable that it is not just monetary transactions that are related to banking employees but also an interweaved set of compeller transactions between people that form the edifice of banking transactions. Therefore, effective interpersonal communication is essential for bank employees. Transactional Style Inventory tools were applied to measure the level of ego states, while structural equation modeling was used to explore the relationship between variables. Results show that respondents exhibit a higher level of adapted child ego and a lower level of creative child ego states. Moreover, nurturing parent, adult ego, and adapted child ego states significantly influence employee commitment and productivity. Based on the findings, the banks were recommended to incorporate developing a recruitment policy that checks the ego states of employees before placing them on the staffing panel of the workplace. Moreover, the research findings also help in using the ego states of employees to design human resource policies that can lead to better interpersonal communication that enhances the productivity of the employees.

在印度的服务提供商中，银行业占主导地位。人际交往技巧在银行业发挥着至关重要的作用，因为无形变量受到沟通的影响。通过事务分析法（TA），银行家可以确保在可接受的自我状态下进行沟通，从而为客户提供更好的服务。本手稿旨在揭示交易分析在决定银行家的承诺和生产率方面的作用。当我们深入研究银行的运作时，就会明白与银行员工相关的不仅仅是货币交易，还有人与人之间交织在一起的强制交易，它们构成了银行交易的大厦。因此，有效的人际沟通对银行员工至关重要。研究采用了交易风格量表工具来测量自我状态的水平，并使用结构方程模型来探讨变量之间的关系。结果显示，受访者表现出较高水平的适应型儿童自我和较低水平的创造型儿童自我状态。此外，养育型父母自我、成人自我和适应型儿童自我状态对员工的承诺和生产率有显著影响。根据研究结果，建议银行在制定招聘政策时，在将员工安排到工作场所的员工小组之前，对其自我状态进行检查。此外，研究结果还有助于利用员工的自我状态来设计人力资源政策，从而改善人际沟通，提高员工的工作效率。

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引用次数: 0

The Thai intrapreneur – A mixed methods study exploring intrapreneurship in Thailand 泰国的企业内部创业者--探索泰国企业内部创业精神的混合方法研究

IF 5.5 Q1 MANAGEMENT

Asia Pacific Management Review

Pub Date : 2024-06-01 DOI: 10.1016/j.apmrv.2024.05.002

Manjiri Kunte

Purpose

This study explores the concept and antecedents of Intrapreneurship among Thai employees in Bangkok, Thailand.

Study design/methodology/approach

The study uses an exploratory sequential mixed methodology. The data were collected from twenty-two in-depth interviews with Thai entrepreneurs and employees, followed by a survey of 648 salaried employees from Bangkok.

Findings

The findings from the interviews suggested that a sense of self-belief and ownership, collaboration in a team, the immediate supervisor, certain characteristics of the job and organization, and a culture of innovation in the organization affected intrapreneurship. The quantitative survey findings confirmed that self-efficacy, entrepreneurial orientation, team cohesion, and organizational support were significantly related to intrapreneurship in Thai companies. Additionally, a split data analysis revealed that the factors affecting intrapreneurship were distinct for the male and female cohorts, whereby self-efficacy was significant in the male data, whereas entrepreneurial orientation and team cohesion were significantly related to intrapreneurship in the female data.

Practical implications

The study proposes the creation of small teams, introduction of role models and internships, and creation of a platform for exchange of ideas as recommendations to encourage intrapreneurship. The study also notes that these initiatives might affect male and female intrapreneurs distinctly.

Originality/value

This is the first notable mixed methods study on intrapreneurship in Thailand. The findings of this study will, therefore, help managers to encourage employees towards intrapreneurial behavior and pave the way for future research on intrapreneurship in Thailand.

研究设计/方法/途径本研究采用探索性顺序混合方法。访谈结果表明，自信心和主人翁意识、团队协作、直接主管、工作和组织的某些特点以及组织中的创新文化都会影响内部创业。定量调查结果证实，自我效能感、创业导向、团队凝聚力和组织支持与泰国企业的内部创业精神有显著关系。此外，分项数据分析显示，影响企业内部创业精神的因素在男性和女性群体中各不相同，男性数据中自我效能感显著，而女性数据中创业导向和团队凝聚力与企业内部创业精神显著相关。本研究还指出，这些举措可能会对男性和女性内部创业者产生不同影响。因此，本研究的结果将有助于管理者鼓励员工的内部创业行为，并为泰国未来的内部创业研究铺平道路。

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引用次数: 0