Investment In Software Research Articles

Strategies for Promoting Rural Digital Party Building from the Perspective of Rural Governance

With the rapid development of digital internet technology, digital party building has gradually developed and become a hot issue in academic circles. The countryside is a late-developing place for the popularization of digital model. Digitalization has brought technical advantages to rural party building, such as online information and data, collaborative information resources and accurate party building services. However, at present, rural areas are facing problems such as weak "key nodes", digital gap, imperfect operation mechanism and insufficient investment in software and hardware. In the new development stage, rural digital party building should: strengthen the "key nodes" of digital party building; Focus on solving the "digital divide" problem; Improve the operation mechanism of rural digital party building; Increase the capital investment in rural digital party building, so as to implement the work of digital party building and improve the governance efficiency of rural party organizations.

Wear monitoring solution for end mills using deep learning and mobile application

Mobile computing can effectively monitor tool life by establishing a relationship between periodically captured cutting tool images and the usefulness level of an end mill. This work presents an image-based deep-learning model to estimate end mill wear parameters and provide tool state feedback to the machine operator. The algorithm estimates the Remaining Useful Life (RUL) and tool wear state from the mobile camera images, viz. initial, intermediate, and worn. The operator captures cutting tool images at predefined intervals on the machine using a mobile camera, macro lens, and tripod arrangement. A pre-trained network, GoogLeNet, is employed for feature extraction, linear regression, and recognizing the tool wear status as RUL. A mobile application is developed to display the wear state and RUL for assisting machine operators in replacing/regrinding decisions. The accuracy and robustness of the proposed model are demonstrated using RMSE (Root Mean Square Error) and Correlation Coefficient (R2) metrics. A set of machining experiments are performed, and it has been shown that the developed module can capture wear states and RUL for end mills. The proposed solutions can be deployed effectively by manufacturing industries for obtaining tool wear information without significant investment in machine vision hardware and software.

Strategic investment strategy for software companies using a multi-criteria decision analysis approach

Strategic investments are crucial for software companies as they determine the direction and growth of the businesses. Parallel to continuous improvements in information technologies, increased customer expectations, and competitive environments, deciding between new investment strategies has become even more important. Despite their prevalence, making these decisions is generally challenging, especially when there are multiple alternatives, conflicting objectives, and a group of decision-makers with different priorities. In this study, we consider this complex issue as a multi-criteria decision-making problem by focusing on a real-life case study from a software company that specializes in selling tools for online education and assessment. We propose a two-level methodology integrating the Best-Worst method (BWM) and Elimination and Choice Translating Reality (ELECTRE-III). In the first step, six criteria that play a role in software investment decisions are defined based on an extensive literature review and expert interviews. Then a group of experts compared these criteria by using BWM, and importance weights were calculated. In the third step, the ELECTRE-III method is utilized to evaluate a set of investment alternatives and provide a ranking. We conclude with insights for both researchers and practitioners who are concerned about strategic investment decisions.

Software investment and organizational change: Evidence from panel data

AbstractTechnological investment is a key managerial decision to make by firms. In recent years, firms increasingly invest in software systems to support big data analytics, digital transformation, and AI, which however do not always pay off. Recent research suggests that software availability may influence entry, at the industry level, by increasing labor productivity, reducing scaling costs, and/or facilitating demand forecasting. However, how these mechanisms through which firms' software investment may affect organizations by inducing various changes is unclear. Insights into these mechanisms require microdata at the firm level over years. We construct a unique panel dataset from 13,335 German firms across industry sectors in 2011–2017 to conduct a firm‐level econometric analysis. We find that, on average, firms' software investment improves demand forecasting but, interestingly, may reduce labor productivity and slow down scaling up. We further propose several organizational contexts in which software investment can be more beneficial to remedy such challenges. Labor productivity is improved only if firms reorganize labor work when making software investment, and scaling costs may be reduced if firms facilitate learning through investments in both software and human capital development. Putting together, this research contributes a new understanding of organizational changes induced by software investment and what contingency factors can make software investment more beneficial in the organizational contexts, to guide managers to make value‐increasing decisions.

An assessment of South African airlines’ growth in the era of Fourth Industrial Revolution technologies: the unexplored dimension

Purpose Aerospace is a demanding technological and industrial sector. Several regulations and policies via innovative digital transformation have been integrated to impact production systems and supply chains, including safety measures. Studies demonstrated that the Fourth Industrial Revolution (4IR) technologies could enhance productivity growth and safety measures. The 4IR role in influencing airlines’ growth is yet to receive in-depth studies in South Africa. Thus, this study aims to investigate the role of 4IR technologies in influencing airlines’ growth in South Africa. Design/methodology/approach This research used a qualitative research method. Primary data were compiled via 56 face-to-face semi-structured interviews with major stakeholders. The study achieved saturation. A thematic method was used to analyse the collected data. Findings Findings reveal the nine major factors influencing South African airlines’ growth in the 4IR era. This includes investment in ergonomics applications and research, governance is driven by 4IR, collaboration and incorporation of 4IR concepts, partnership with drone technology and high precision and efficiency with 4IR. Others are reskilling and upskilling, investment in 4IR software, policies to promote 4IR usage in the industry and policies to reduce human interface. Originality/value Understanding the relative significance of 4IR technologies’ role in airlines’ growth can assist critical stakeholders in promoting innovative policies and regulations tailored towards digitalised aerospace. Thus, the study contributes to strategies to improve digital innovation, airline growth and safety as components of the air travel demands in South Africa.

Industrial redesign in leather tanning processes

The work was focused on evaluating and redesigning processes in the leather treatment production system. Leather treatment is a booming industry in the Andean regions of Latin America. In this sense, this study is based on a tannery located in Peru. This work is dedicated to developing an approach to improve processes based on optimizing personnel movements. The correct study of the planning of the areas where the actions that aim to obtain leather are executed using strategies that do not require expensive investments in tools or software since optimizing processes without making significant capital investments is sought.

The use of taxonomic analysis for the purposes of HR analytics

The article is devoted to the study of the effectiveness of an enterprise’s HR strategy, taking into consideration the conditions of digitalization by applying taxonomic analysis as a component of HR analytics. The research is based on the HR concept of a new type according to the maturity model of HR-analytics, which determines the directions of support for systematic analytics and the implementation of its goals regarding the basis for making effective management decisions. The directions of applying taxonomic analysis in various areas are analyzed, in particular, to determine the level of solvency, to assess a company's development strategy, to study the effectiveness of management of the economic potential of enterprises, to assess the ability of an enterprise to implement an innovative strategy, etc. The expediency of implementing the taxonomic analysis method in the field of HR analytics, taking into account digitalization factors and HR metrics, is substantiated. Nine indicators are chosen for the calculation of the taxonomic indicator, namely: an ICTS subindex of the Global Innovation Index and investments in software and databases in Ukraine, which made it possible to take into account the external factors of digitization; return on capital as an internal factor in digitalization; the staff turnover ratio, the level of working time loss, the average length of service, the average salary at the enterprise, profit per employee. According to the methodology, the researched indicators of the effectiveness of the HR strategy in the conditions of digitalization are divided into stimulators and destimulators. A graphic representation of the dynamics of the taxonomic indicator of the HR strategy effectiveness is given for the period from 2013 to 2022. It is recommended to implement targeted approaches to building a road map of HR digitalization, which will increase the efficiency of personnel management processes.

Inhibitors to the Adoption of Building Information Modelling in Modular Construction: A Case Study of the Nigerian Construction Industry

Building information modelling (BIM) adoption transforms how construction projects are delivered. Modular construction (MC) is a modern construction method that drives continuous improvement and value addition globally. BIM and MC offer enormous benefits in enhancing project delivery and attaining sustainable construction. This is a major driving force causing the drift from traditional methods to a more digitised approach anchored on technology. Despite these benefits, the level of sophistication in project delivery and the application of these innovative methodologies are low and housing construction projects are delivered with poor performance outcomes in developing countries like Nigeria. This study assessed the inhibitors to the use of BIM in driving MC and the measures for improving the adoption of BIM in MC project deliveries in Nigeria. A well-structured quantitative questionnaire was administered to construction experts using Snowball sampling techniques via electronic means to collect data. With a response rate of 70% and a reliability index of above 0.80, the collected data were analysed using frequencies, percentages and mean item scores. It was found that the level of BIM and MC was high, but BIM adoption in MC was low. The inhibitors to this low adoption level are the high cost of investment in hardware and software, the comfort with the existing methods and resistance to change, the lack of management support, the complexity of BIM software, the lack of interest in sharing information among stakeholders, the problems with collaboration and the legal issues with multiple designs and fabrication. It is recommended that collaboration between construction and technology firms be encouraged to improve BIM application in MC for better productivity and project outcomes. The government should support the use of modern methodologies in the delivery of projects to help improve infrastructure provision, value addition and citizens’ well-being.

MODELLING AND SIMULATION AS A SERVICE (MSaaS) - EVOLUTION OF THE ALLIED FRAMEWORK WITHIN NATO

NATO Modelling and Simulation Group (NMSG), the Alliance's modelling and simulation body, has focused its efforts in recent years on developing the concept of Modelling and Simulation as a Service (MSaaS), which aims to solve the difficulties in terms of cost and interoperability between existing modelling and simulation systems within Member States. The concept is based on cloud computing and Service Oriented Architecture (SOA) and its main objective is to assure improved flexibility, better accessibility and scalability, with lower costs for modelling and simulation applications. Advances in service-oriented architecture (SOA) and cloud computing are an opportunity to improve the use of modelling and simulation capabilities within NATO. MSaaS is based on the idea of being able to use a computer product without a major investment in hardware, software, staff and infrastructure. Thus, the military user can be situated in a central location, while the services offered can be available through the network. The research and development activities of MSaaS within NATO were undertaken by the NATO Modelling and Simulation Group (NMSG) on the basis of a multi-stage structured strategy, which started in 2013. At present, the implementation strategy is in MSaaS Specification and Validation phase, to be completed in 2022.

Economic impacts of in-house and packaged software investments: the influence of software investment opportunities

PurposeSoftware has become increasingly important in business. However, the value of aggregate in-house and packaged software investments and the influence of an industry's software investment opportunities (SIOs) are poorly understood in the literature. This study addresses this research gap and proposes that an industry's SIOs play an essential role in the economic impacts of industry in-house and packaged software investments.Design/methodology/approachA model of the economic impacts of in-house and packaged software investments at the industry level under different SIOs is developed and empirically tested based on a panel dataset of private industries in the USA between 1998 and 2020.FindingsThe results show that with the increase in the number of SIOs in an industry, the economic performance of in-house software investments increases, while that of packaged software investments decreases.Originality/valueBy highlighting the role of SIOs in moderating the economic performance of in-house and packaged software, this study shows the critical role of the information technology (IT) environment in understanding software's economic value.

Sources of transport sector labor productivity performance in industrialized countries: Insights from a decomposition analysis

This study examines patterns and sources of growth in the transport sector's labor productivity across 13 industrialized countries over the period 2000–2015. Through decomposition analysis – specifically, the growth accounting method and industry origin analysis – the study makes three principal findings. First, total factor productivity growth plays a crucial but often underleveraged role in driving the sector's growth and catch-up on labor productivity. Second, digital transformation – especially investment in software and database assets – is a significant source of the sector's labor productivity growth and catch-up, while innovation-related capital has a complementary effect. Third, subsector-level labor productivity improvement is the major driver of the sector's overall labor productivity growth, while the growth contribution of labor reallocation among subsectors is insignificant. The article concludes with a discussion of policy insights and implications.

Investigating the future of model-based construction in the UK

PurposeAlthough data rich building information models have been widely adopted in the Architecture Engineering and Construction (AEC) industry in the United Kingdom (UK), use of 2D drawings on site for construction is still the norm. The ability of 2-dimensional (2D) drawings to convey complex 3-dimensional information is limited and requires interpretation from operatives, and 2D drawings can be quickly superseded by model updates. Although constructing directly from a model has been adopted in the aerospace and automotive industries, its use in construction is in its infancy. This research therefore aims to investigate the potential for, and barriers to, model-based construction in the UK.Design/methodology/approachThis research uses a qualitative approach, thematically analysing 13 semi-structured interviews with UK-based construction professionals who have experience of paperless or model-based construction.FindingsAlthough model -based construction has been implemented to a limited extent on some civil engineering projects; research and investment in software, network capacity, legal and contractual issues, and cultural and human factors will need to be considered before model-based construction can be implemented more widely.Originality/valueThe research contributes to an understudied, emergent area of construction practice and outlines hurdles that need to be understood and overcome before more widespread adoption of model-based construction can take place.

Research on the Effects of Software Reuse in Project Development

Software reuse is the process of reusing software resources. In a new application, all stages of the software development process. Given the high cost and difficulty of building high-quality software, the idea of leveraging earlier software investments is intriguing; yet, software reuse has not shown to be as effective as anticipated and is not widely or systematically adopted in business.

The digital transformation of logistics

Digital transformation of logistics has emerged into the lexicon of the industry but lacks definition and actionable tactics. This paper offers a definition of the term and creates a context for how investments in software and hardware solutions can be applied as a strategy toward a more interoperable logistics community. Tactics and implementation strategies are described along with examples of past, current and future digital transformation initiatives from different facets of logistics. Tactics and strategies are shared with the intent to better prepare organisations to take advantage of the next generation of artificial intelligence (AI) and machine learning (ML) that are evolving rapidly.

A Review of Incremental Reuse Method in Software Reuse Process

Abstract: In the late 1960s, the concept of software reuse was proposed. The legacy of software engineering process shows that the scope and field of software reuse was not particularly new. However, it is considered that software reuse is in its primary stages and has yet to reach its full capacity. The utilization of software components from entire stages of the software engineering process in new applications is called as software reuse. Given the economically costly and difficulty of building qualitative software, repurposing prior software investments is enticing. We propose that software reuse should be considered as part of a fully systematic approach that considers a wide range of technological, economical, managerial, organisational, and legal considerations, and we wrap up with a synopsis of the important research issues in all these verticals. This paper summarises our progress in software reuse research. Keywords: Software Reuse, Incremental Reuse Method (IRM), Reuse Process, Artifact, Software Component

COVID-19, economic crises and digitalisation: How algorithmic management became an alternative to automation.

The COVID‐19 crisis witnessed a major rise in investment in software for the digital organisation and rationalisation of work, while investment in robotics is continuously lagging behind expectations. This article argues that we can understand this development as the continuation of the rise of algorithmic management as a technological fix for profitability crises. Thus, in the face of falling wage rates and a structural overaccumulation of capital since the 1970s, algorithmic management has become an alternative to automation. The article reconstructs the history of algorithmic management in connection to economic crises. This allows for periodisation of the rise of algorithmic management from 'computer‐integrated manufacturing' to remote work in four waves. In times of crisis, algorithmic management functions as a substitute for investment in 'tangible capital' such as robots. Structural economic forces thus interact with labour conflicts at the company level, shaping the rise of algorithmic management.

The impacts of industry environment on software insourcing, outsourcing, and buying

PurposeNowadays, an increasing number of firms choose to develop proprietary software, instead of buying packaged software. What factors will affect different types of software investments? According to the environment-strategy alignment research, environment should be an influential factor. However, environment's role has received scarce attention in the literature. The authors' study addresses this research gap by investigating how industry environment affects different types of software investments. The study identifies three types of software investments (software insourcing, outsourcing, and buying) and examines how the characteristics of the industry environment (including industry munificence, dynamism, and concentration) influence each software investment.Design/methodology/approachThe generalized least squares (GLS) model and the ordinary least squares with panel-corrected standard errors (OLS-PCSE) model are applied to test the hypotheses, based on industry-level panel data from the US Bureau of Economic Analysis (BEA).FindingsThe analysis shows that industry munificence, dynamism, and concentration have different impacts on software insourcing, outsourcing, and buying, respectively.Originality/valueThis study classifies software investment into three types – software insourcing, outsourcing, and buying and investigates how the industry environment affects them. The findings suggest that research should distinguish among software insourcing, outsourcing, and buying due to their different characteristics.

Music Singing Based on Computer Analog Piano Accompaniment and Digital Processing for 5G Industrial Internet of Things

At present, most professional music colleges and universities have made large-scale investment in computer software and hardware equipment and have also continuously opened various relevant courses. However, how to give full play to the advantages of computer music at the software level and make software and hardware systems suitable for music education application is still a subject being explored. The industrial Internet of Things turns every link and equipment in the production process into a data terminal, comprehensively collects the underlying basic data, carries out deeper data analysis and mining, and improves efficiency. To adapt to the trend of the times, digitization is the inevitable trend of the development of music accompaniment, and the deep integration of computer is an important way to realize digitization. Combined with the basic music theory and digital processing method, this paper designs the virtual piano auxiliary accompaniment and realizes the digital music accompaniment of artificial intelligence through digital signal processing. This paper will start with the auditory effect of auxiliary singing, take the rhythm and style of piano auxiliary accompaniment as the research object, build the accompaniment generation tool through the piano music simulation system model, and generate the accompaniment chord of the main melody by extracting the style, treble, and other characteristics of the main melody. The simulation results show that the frequency response is evenly distributed, the model effectively uses the harmonic structure information, and the extracted feature dimension is only 88. The reduction of feature dimension can save the time of subsequent processing and has the characteristics of real time, automation, embedded (software), security, and information interoperability.

ASAS-NANP symposium: mathematical modeling in animal nutrition: limitations and potential next steps for modeling and modelers in the animal sciences.

The field of animal science, and especially animal nutrition, relies heavily on modeling to accomplish its day-to-day objectives. New data streams ("big data") and the exponential increase in computing power have allowed the appearance of "new" modeling methodologies, under the umbrella of artificial intelligence (AI). However, many of these modeling methodologies have been around for decades. According to Gartner, technological innovation follows five distinct phases: technology trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity. The appearance of AI certainly elicited much hype within agriculture leading to overpromised plug-and-play solutions in a field heavily dependent on custom solutions. The threat of failure can become real when advertising a disruptive innovation as sustainable. This does not mean that we need to abandon AI models. What is most necessary is to demystify the field and place a lesser emphasis on the technology and more on business application. As AI becomes increasingly more powerful and applications start to diverge, new research fields are introduced, and opportunities arise to combine "old" and "new" modeling technologies into hybrids. However, sustainable application is still many years away, and companies and universities alike do well to remain at the forefront. This requires investment in hardware, software, and analytical talent. It also requires a strong connection to the outside world to test, that which does, and does not work in practice and a close view of when the field of agriculture is ready to take its next big steps. Other research fields, such as engineering and automotive, have shown that the application power of AI can be far reaching but only if a realistic view of models as whole is maintained. In this review, we share our view on the current and future limitations of modeling and potential next steps for modelers in the animal sciences. First, we discuss the inherent dependencies and limitations of modeling as a human process. Then, we highlight how models, fueled by AI, can play an enhanced sustainable role in the animal sciences ecosystem. Lastly, we provide recommendations for future animal scientists on how to support themselves, the farmers, and their field, considering the opportunities and challenges the technological innovation brings.

Investment Areas to Enhance Public Employee Resilience during the Coronavirus Disease 2019 (COVID-19): Evidence from Iran

This study aims to investigate the areas of investment that the human resources management of the Iranian public sector has invested in for improving employees' resilience in the COVID-19 pandemic period. This study is qualitative and the qualitative content analysis is used to analyze the data. The qualitative content analysis is used to analyze the data. According to findings, essential areas for investment to improve employee resilience are hardware investments, software investments, and wetware investments.While increasing the knowledge of employee resilience, this qualitative study provides valuable and practical implications for policymakers and managers in the public sector.