Building Acquisition Management Capability to Improve Firm Performance in Acquisitions

In the past two decades, the number of cross-border mergers and acquisitions in ASEAN has progressively expanded as the region has become a desired economic market for trade and investment. Therefore, this study aimed to identify the factors contributing to the success of acquisitions by corporations. It investigates the role of acquisition management capability with strategic integration and acquisition. The non-probability sampling strategy was used to collect information from 51 firms. With a five-point Likert scale, a systematic questionnaire was designed to test the latent variables by employing confirmatory factor analysis. The quantitative method of Structural Equation Modeling was used in the analysis. The results show that the structural model had a Goodness of Fit Index value that indicates all three latent variables and independent variables were valid. The findings indicate that acquisition management capability have a central role in advancing the overall integration of the acquiring firm in the ASEAN context.

Psychological Health Assessment Model of Enterprise Employees Based on DNN Technology

All enterprises gradually recognise the importance of employees’ healthy psychology to business activities in order to improve their own economic level and occupy a certain leading position in the economic market. The main factors affecting employees’ psychological health are used as input samples in this paper, and a network model of enterprise employees’ psychological health prediction based on DNN is developed. To form a specific set, the psychological health indicators are separated from the complex test items. The key influencing factors in psychological health assessment are chosen as input vectors, and the DNN algorithm’s output results are obtained, analysed, and compared. Following sample training, the artificial NN’s error between predicted and measured values is only 3.55 percent, achieving the desired effect. The DNN principle is used in this paper to create a mathematical prediction network model based on an analysis of psychological factors affecting employees in businesses. The calculation of the final result of the prediction system is simple and flexible when the parameters of the NN are changed, and the network model’s prediction efficiency and accuracy are greatly improved.

СИСТЕМАТИЗАЦІЯ ВИТРАТОУТВОРЮЮЧИХ ЧИННИКІВ ДЛЯ УПРАВЛІННЯ ВИТРАТАМИ ПІДПРИЄМСТВА НА ТАКТИЧНОМУ ТА СТРАТЕГІЧНОМУ РІВНЯХ

The article attempts to substantiate the key approaches to the systematization of cost-driving factors from the enterprise cost management perspective (tactical and strategic) and offers a definition to a factor concept. The study presents the existing scientific approaches to the classification of cost drivers as well as an interpretation of cost-driving factors. Groups of structural factors within internal and external environment that affect enterprise costing have been identified along with revealing the character of such influence, i.e. whether they provide a direct indirect effect on the company expenditures. Given the tactical and strategic management objectives, the authors suggest systematization of all cost drivers into two groups. In particular, tactical management covers the following factors: output scale, product range, company cost management methods, qualification of personnel, and depreciation accrual. Within the scope of this study, strategically critical factors are represented by organizational business pattern of production, technology level, lack of brand awareness for domestic products, inflation rate, average salary range, low solvency, high costs for raw materials and energy, high tolls, import dependency, strong market competition, low demand, lack of government support, excessive tax burden, frequent changes in tax legislation, high loan interest rates, unfavourable investment environment, poor networking between domestic enterprises in complementary industries, small share of medium-sized businesses or small business alliances. In addition, in the frameworks of strategic cost management, the study offers to classify the cost drivers into the following groups: economic, market- or tax-based, financial and systemic. Apart from that, the relationship between individual cost-driving factors has been revealed. The findings argue that strategic cost management has a number of limitations associated with certain challenges to attain accuracy in forecasting change in factors for successive periods.

Economic Market Fluctuation Model Based on Internet of Things Technology

In order to explore the impact of the Internet of Things technology on economic market fluctuations and the analysis effect of the Internet of Things technology on economic market fluctuations, this paper uses the Internet of Things algorithm to improve the economic fluctuation model. Moreover, this paper uses the Internet of Things algorithm to locate economic transactions and performs data processing to optimize the intelligent network system to improve the operating effect of the economic system. In addition, this paper improves the sensor node algorithm and proposes to use the weighted value of network node density to balance the positioning problem caused by the unbalanced distribution of network nodes in the detection area. Finally, this paper analyzes the market economy volatility model through the Internet of Things technology, combined with simulation experiments to explore the application of the Internet of Things technology in the economic market volatility model. Through experimental research, it can be known that economic market fluctuation models based on Internet of Things technology can play an important role in market economic analysis.

A Hydrologic Monitoring Dataset for Food and Water Security Applications in Central Asia

From the Hindu Kush Mountains to the Registan desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The FEWS NET Land Data Assimilation System (FLDAS) global and Central Asia data streams described here combine meteorological reanalysis datasets and land surface models to generate routine estimates of snow-covered fraction, snow water equivalent, soil moisture, runoff and other variables representing the water and energy balance. This approach allows us to fill the gap created by the lack of in situ hydrologic data in the region. First, we describe the configuration of the FLDAS and the two resultant data streams: one, global, at ~1 month latency, provides monthly average outputs on a 10 km2 grid from 1982–present. The second data stream, Central Asia, at ~1 day latency, provides daily average outputs on a 1 km2 grid from 2001–present. We describe our verification of these data that are compared to other remotely sensed estimates as well as qualitative field reports. These data and value-added products (e.g., anomalies and interactive time series) are hosted by NASA and USGS data portals for public use. The global data stream with a longer record, is useful for exploring interannual variability, relationships with atmospheric-oceanic teleconnections (e.g., ENSO), trends over time, and monitoring drought. Meanwhile, the higher spatial resolution Central Asia data stream, with lower latency, is useful for simulating snow-hydrologic dynamics in complex topography for monitoring snowpack and flood risk.

Analysis of the Wear Process of the Elements in the Braking System of Heavy Trucks

Today's commercial vehicles work in a very competitive environment, in an extremely active economic market and the requirements for the delivered performance make it imperative to study in detail each component element. In practice, all these aspects are found in the process of wearing the elements of different systems. Moreover, major changes are expected for the near future of motor vehicles in order to improve the ecological balance both by reducing the pollutant emissions of the propellants and by improving the percentage of recyclability and reduction of waste from maintenance (liquids and solutions such as oils, antifreeze or solutions with different detergents). In order to identify solutions to improve the mentioned problems, the current study analyses the types of wear identified in the elements of the braking system of commercial vehicles and their main factors of influence. The study is based on data obtained during analysis during operation for a number of trucks with different configurations.

hGLUTEN Tool: Measuring Its Social Impact Indicators

hGLUTEN is a technological solution capable of detecting gluten and spoiled food. We measured the social impact of the hGLUTEN tool using two Likert scale surveys with two groups: professionals (engineers/chefs) and end-users. These data have been assessed in accordance with the social impact indicators defined for the Key Impact Pathways introduced by the European Commission for Horizon Europe and the criteria of the Social Impact Open Repository (SIOR). A total of 85% of users, 100% of engineers and 68% of professional chefs consider it very relevant to participate and give their opinion in research projects, which shows the increasingly high level of involvement of the general population. A total of 88% of users were unaware of other applications that detect gluten and were more dependent on guidelines provided by allergy associations and expiry dates of foodstuffs. In addition, only 5% of professional chefs said they were aware of other technology capable of detecting gluten in food, which may indicate a large economic market and good commercialisation possibilities for the tool in the future. Finally, the inclusion of tools to motivate users to promote it has been identified as an area for improvement, which could mean that it should be made more visible in the media to increase its impact and influence.

Impacts of Climate and Environmental Change on Bean Cultivation in China

The impact of human-caused environmental pollution and global climate change on the economy and society can no longer be underestimated. Agriculture is the most directly and vulnerably affected sector by climate change. This study used beans, the food crop with the largest supply and demand gap in China, as the research object and established a panel spatial error model consisting of multiple indicators of four factors: climate environment, economic market, human planting behavior and technical development level of 25 provinces in China from 2005 to 2019 to explore the impact of climate environmental changes on the yields of beans. The study shows that: (1) The increase in precipitation has a significant positive effect on bean yields; however, the increase in temperature year by year has a significant negative effect on bean yields; (2) carbon emissions do not directly affect bean production at present but may have an indirect impact on bean production; (3) artificial irrigation and fertilization behavior on bean production has basically reached saturation, making it difficult to continue to increase bean yields and (4) the development of technology and human activity is a mixed blessing, and the consequent inhibiting effects on bean production are currently unable to offset their promoting effects. Thus, when it comes to bean cultivation, China should focus mainly on the overall impact of environmental changes on its production, rather than technical enhancements such as irrigation and fertilization.

How Do Teleworkers and Organizations Manage the COVID-19 Crisis in Brazil? The Role of Flexibility I-Deals and Work Recovery in Maintaining Sustainable Well-Being at Work

The COVID-19 pandemic has impacted the economic market and labor contexts worldwide. Brazil has suffered one of the worst social and governmental managements of the COVID-19 crisis, forcing workers and organizations to develop coping strategies. This environment can affect both well-being and performance at work. Sustainable well-being at work refers to different patterns of relationships between performance and well-being. It may include eudaimonic (e.g., Meaning of Work—MOW) or hedonic (e.g., emotions) forms of well-being. This study tests the moderating role of recovery from work stress in the relationship between flexibility i-deals and patterns of sustainable well-being at work in Brazilian teleworkers. We relied on two studies to achieve this objective. In Study 1, conducted during the pandemic’s first outbreak in Brazil (N = 386), recovery experiences moderated the relationship between i-deals and clusters formed by performance and MOW (eudaimonic happiness). In Study 2, conducted during the second outbreak (N = 281), we identified relationships between clusters of emotions (hedonic happiness) and MOW (eudaimonic) with performance. The results supported the idea that recovery experiences moderated the relationship between i-deals and patterns of sustainable well-being at work differently. Our findings have implications for Human Resource Management and teleworkers, especially for employee behaviors to deal with stress.

A Common Market Problem Becomes More Common: the Trans-Tasman Proceedings Act 2010

<p>As part of a wider process of economic integration and the move towards a single integrated economic market, Australia and New Zealand entered into bi-lateral treaty in 2008 in order to resolve existing issues with the reciprocal enforcement of civil judgment which had arisen between the two countries. Labelled the “Christchurch Agreement” this treaty was incorporated by both countries into their domestic law in 2010 and now governs the allocation of disputes between Australia and New Zealand, where the parties are located within the common market of Australia and New Zealand and inter-state enforcement of civil judgments more generally. The Trans-Tasman Proceedings Act 2010 (Cth) and (NZ) (“TTPA”), will arguably provide significant benefits by reducing barriers to trade and improving the economic prosperity of both countries. However it is argued that, similar to other common market reciprocal enforcement schemes (such as the Brussels Model in the European Union), Australia and New Zealand failed to consider the impact of the outer world problem. The outer world problem is a recurring theme in common market arrangements, and results from a failure to provide generic proportionate jurisdictional test for cases involving foreign defendants sued in a common market state. The result is excessive jurisdictional rules within a particular state can potentially result in proceedings being retained where there is a strong argument the dispute is more closely connected with another forum. The resulting judgment (should judgment in the plaintiff’s favour be granted), can then be quickly enforced throughout the common market (specifically New Zealand) to the disadvantage of the defendant. The outer world problem is clearly present under the TTPA scheme, beginning in Australia and cumulating in enforcement of the judgment in New Zealand. It remains present even in the case of international commercial contract disputes. This is unfair and discriminatory towards foreign defendants, and arguably justifies reform, or at least discussion and justification of this approach.</p>