High-technology Companies Research Articles

Institutional environment for the development of regional high-technology industries

Introduction. The effective development of high-technology industries is ensured by a high-quality institutional environment formed at both federal and regional levels. Most works in this field lack a systematic approach and leave room for the further study of the institutional environment for the development of regional high-technology industries. Purpose. The identification of the minimum required framework of the institutional environment that ensures the development of regional high-technology industries. Methodology. In this work we used the following general and special methods: analysis, synthesis, induction, deduction, generalisation, comparison, economic analysis, content analysis, and tabular interpretation of empiric and factual information. Results. We identified key political, legal, economic, and social institutions that influence the development of regional high-technology industries. Conclusions. The institutional environment is a complex and multidimensional system of institutions and their interactions that influence the activities of all economic agents, including innovative and high-technology companies. Therefore, it is necessary to ensure the formation of high-quality institutions at both federal and regional levels that will make the interactions in the field of high technologies predictable, decrease transaction costs, and so on.

Use or nonuse? The role of possessed power and realized power on innovation

Power is a central element and salient research topic within supply chain management, and it is also regarded as a key attribute influencing innovation in the supply chain. However, there are still disputes about the consequences of power and whether it should be used. Given this, we examine the relationship between power and innovation, and attempt to explore how to use power to improve innovation performance. In order to better understand power and its influence, we distinguish between possessed and realized power. Using the panel data collected in the Chinese high-technology companies (2014–2018) and controlling for contingencies, we found that there are positive relationships between possessed power and exploitation, exploration, especially the collaborative innovation of them, and these relationships are negatively moderated by financial slack. Surprisingly, we find inverted U-shaped relationships between realized power and exploitative, explorative and collaborative innovation. That is, the excessive use of power begins to show diminishing innovation returns. These findings offer new insights into power and its use in supply chain relationships by distinguishing possessed and realized power, and enrich the literature on supply chain management and innovation.

The effect of emotional leadership and job security on employees' mental health

We examined the impact of emotional leadership on employees' mental health by establishing a cross-level theoretical model to test this relationship as a function of employees' sense of job security, selfdirected learning, and organizational identification. The research sample consisted of 304 employees of 10 high-technology companies in China. Results show that emotional leadership was positively associated with employees' mental health, and that job security mediated this relationship. Organizational identification and selfdirected learning positively moderated the relationship between job security and employees' mental health, resulting in a moderated mediation effect on the model. The conclusions of this study have implications for improving employees' mental health via interactions with emotional leaders.

How Attributes of Organizational Structure Affects Knowledge Management Processes in High-Technology Companies?

Purpose: The article aims to identify links between attributes of organizational structure and knowledge management processes in high technology companies. Approach/Methodology/Design: The research was conducted in 100 Polish high-tech companies. Findings: The results show that high-tech enterprises carry out different number of sub-process of knowledge management in different combinations. Surveyed companies confirm that different structural features are needed depending on the phase/sub-process of knowledge management. It is recommended to redesign the organizational structure in such a way that it corresponds to the key knowledge management processes as much as possible. Flexibility was found to have the most supportive effect on five of the seven knowledge management sub-processes studied. Practical Implications: The results can serve as a guide for managers in improving the organizational structure for knowledge management needs. Originality/Value: The attributes of organizational structure supportive and inhibiting knowledge management processes for high-tech companies were identified.

IPO Success of High-Technology Companies

Purpose: The research aimed to verify whether high-technology companies are more successful during IPO than other low-technology peers. Design/Methodology/Approach: We evaluated the IPO success using two measures: 1) relation of capital collected during IPO to the equity capital at the year-end of IPO, 2) underpricing. The analysis was based on the IPO of 334 companies on the Warsaw Stock Exchange in Poland from 2004 to 2018. According to Eurostat methodology, we measured technology level, and we divided companies into two groups, HT (high-tech) and LT (low-tech). Models were executed separately for the whole sample but also for each group. As control variables we have used, debt, profitability, size, and the bull market indicator. Findings: Our empirical results confirmed that the more technologically advanced company (in terms of the sector in which the company operates), the lover success of IPO. The HT companies collect a relatively smaller amount of capital during IPO, and the underpricing is higher in the HT group. We link the results with a higher asymmetry of information. Practical Implications: HT companies should pay special attention to lower the information asymmetry before the IPO by disclosing precise information about future development for betted risk evaluation. HT should also raise a small amount of capital during the IPO and make secondary issues later when the company is more recognized in the market. Originality/value: The previous research mainly focused on how going public impacts the innovation activities post-IPO. We did not find the previous literature studies on the IPO success of HT and LT firms. Some were related to underpricing, however, we extended measuring IPO success to additional indicator.

Globalization from Below: Labor Inequality in the German Shipbuilding Industry, 1960-2000

This study examines how globalization affected employment changes in the German shipbuilding industry in the second half of the 20th century. Over four decades, as a response to global competition originally large and labor-intensive shipyards in the northwest of Germany evolved into lean and nimble high-technology companies. Our findings based on 28 oral history interviews with former staff of two leading shipyards show that this large-scale industry transformation is a hitherto hidden history of labor mobility, migration and evolving dimensions of diversity in the workplace. Allowing for a look at globalization from below, the narrations reveal structural and subjective implications on workforce hierarchies and on different workers’ roles and positions. We identify five patterns of social exclusion and inequality between and within groups of workers with and without migrant backgrounds that have not been documented before.

Exploitative Leadership and Counterproductive Work Behavior: A Discrete Emotions Approach

Integrating appraisal theories of discrete emotions and theory of emotion regulation, we seek to examine the effects of exploitative leadership on certain types of counterproductive workplace behavior (CWB) through discrete emotions and the moderating effect of cognitive reappraisal. Using time-lagged data from 440 full-time employees of a high-technology company in North China, our results revealed that exploitative leadership was positively related to approach-oriented CWB and avoidance-oriented CWB. Moreover, we found that anger mediated the relationship between exploitative leadership and approach-oriented CWB, whereas fear mediated the relationship between exploitative leadership and avoidance-oriented CWB. Further, cognitive reappraisal attenuated the positive effects of exploitative leadership on anger and fear and the indirect effects of exploitative leadership on approach-oriented CWB (via anger) and avoidance-oriented CWB (via fear). Implications for theory, practice, and future research are also discussed.

Transitions in Project Management Offices: A Framework Relating Functions, Success Factors and Project Performance in a High-Technology Company

This paper aims to present and analyze the transitions in operational activities and the performance of a Project Management Office (PMO) in a technology-based company through a longitudinal case study. The paper discusses functions, tensions, success factors, indicators, and performance and how they drive the major changes faced by the PMO. The results demonstrated that political tensions, more than performance, explained PMO changes. Tensions are originated from both requirements from project stakeholders that were not addressed and success itself, meaning that stakeholder dispute for capitalizing on the success’s honors and benefits. Issues about centralization, project performance, and focus on stakeholders’ demands seem to be central for designing the role and functions of project management offices in the studied high-technology company. In the end, a theoretical framework presents the results of the case study in terms of factors influencing PMO transitions.

Investigating the mechanism linking task conflict with employees’ innovative work behavior

PurposeThe effect of task conflict on innovative work behavior has yielded inconsistent results pointing to the need to examine the conditions under which task conflict is helpful for employees’ innovative work behavior. This study aims to develop a comprehensive model linking task conflict and innovative work behavior through constructive conflict, positive conflict value, cognitive flexibility and psychological safety.Design/methodology/approachData were collected from 316 supervisor–subordinate dyads working in software development and high-technology companies located in Saudi Arabia. The research model was tested using partial least squares approach.FindingsResults show that constructive conflict mediates the relationship between task conflict and innovative work behavior. Moreover, positive conflict value and cognitive flexibility mediate the effect of constructive conflict on innovative work behavior. Finally, psychological safety positively moderates the effect of positive conflict value and cognitive flexibility on innovative work behavior.Originality/valueThis study suggests that constructive conflict, cognitive flexibility, positive conflict value and psychological safety are important mechanisms that explain the link between task conflict and innovative work behavior.

Intelligent FinTech Data Mining by Advanced Deep Learning Approaches

With the progress of financial technology (FinTech), real-time information from FinTech is huge and complicated. For various fields of research, identifying intrinsic features of complex data is important, not limited to financial big data. Reviewing previous studies, there are no suitable methods to deal with complex financial data. General methods are traditionally developed from statistics and machine learning. They are usually in some shallow model forms, which cannot fully represent complex, compositional, and hierarchical financial data features. Due to above drawbacks, this study tries to address the problem by advanced deep learning (DL) methods. In DL more layers will increase the power for abstract data representation. Recently, DL has achieved state-of-the-art performance in a wide range of tasks including speech, image, and vision. DL is effective in learning increasingly more abstract representations in a layer-wise manner. That just meets the characteristic of financial data. This study applies newly developed DL networks, the deep canonically correlation analysis and deep canonically correlated autoencoders to perform FinTech data mining. To test the proposed model, this study employed financial statement data regarding many listed high technology companies in Taiwan stock markets. The computation of deep learning is leveraged by multiple graphics processing unit. Our systems and traditional methods are compared by the same data. Empirical results showed that our systems outperform traditional techniques from statistics and machine learning.

Memahami Dinamika Bekerja dalam Ketidakpastian: Tinjauan Fenomenologis Pengalaman Bekerja Pengemudi Ojek Online

Employees of high technology company often facing rapid and unpredictable changes. This qualitative research aims to explore further how workers with high uncertainty working environment develop their strategies to be survived in this kind of environment. Online ojek driver works in high uncertainty environment where they have no clear employment status. The technology company who employs them only see them as a business partner which their relationship with the company could be terminated anytime. This qualitative research is conducted with phenomenological approach. Six ojek online driver respondents were chosen with minimum criteria: has been working in this field minimum 1 year, play a role as the main income earner in the family, and has the main job as online motor driver. Through a qualitative method with phenomenological approach, data analyzed by data reduction process resulted in five main themes: environmental uncertainty, task identity, values, strategy, and hope and themes of strategy to overcome those work situations and nature. Then the researcher developed an essential description or comprehensive construction about the meaning and the essence of the subjects’ experiences.

The impact of innovation strategies on business performance: practices in high technology companies in Turkey

Innovation efforts aim to attain important competitiveness by improving performance criteria. It has led to very strong ties between innovation and performance, which is also accepted by the recent business understanding. The purpose of the current study, which is designed in compliance with this understanding, is to examine the effect of innovation strategies on business performance in enterprises using high technology. Innovation strategies consist of 6 dimensions: proactive strategy, risk-oriented strategy, defensive strategy, future-oriented strategy, offensive strategy, and analytical strategy. Business performance was measured as product performance, employee-based performance, customer-based performance, financial performance, and process performance. The study involved the innovation strategies and business performance scale developed by Morgan and Strong (1998), Chandy and Tellis (1998), and Eskici (2020). The current study conducted a survey on 346 managers of companies operating in Turkey and using high technology. The obtained data were analyzed with the help of JAMOVI and SPSS 26.0 programs. Exploratory factor analysis, confirmatory factor analysis, Pearson correlation, and regression analysis methods were used in empirical analysis. The result determined that innovation strategies are effective on business performance. In other words, future-oriented strategy is effective on the product, customer-based, employee-based, financial, and process performances of enterprises. On the other hand, it was determined that future-oriented strategy and risk-oriented strategy are not effective on enterprises' product, customer-based, employee-based, financial, and process performances. In addition, offensive, analytical, defensive, proactive, and risk-oriented strategies are ineffective in process performance. Analytical, defensive, future-oriented, and proactive strategies are effective on product performance, customer-based performance, and financial performance of businesses. As a result, it was determined that innovation strategies affect customer-based performance (R2=0.687) and financial performance (R2=0.701) of companies more.

The differential practices of project management offices for supporting new product development in high-tech companies

The article, through presenting a company's project management office (PMO), argues about practices a PMO must establish for supporting new product development (NPD) in high-technology companies. A holistic case-study was performed where data gathered comes from interviews, direct and participant observation, and document analysis. The practices identified differ from the current literature about the PMO functions. The whole set of functions performed by the described PMO responds to specific processes an NPD project asks for. It begins monitoring, analysing, and systematising product requirements to develop project schedules. During project execution, it supports configuration management through engineering change management. When prototyping, it carries on provisions of the necessary materials and subcontracted processes for assembling and testing. These PMO functions are compared to the current PMO literature. It is suggested that the functions undertaken by the PMO can enhance the theoretical options for structuring PMOs in NPD-based companies avoiding mimicry dysfunctions.

The differential practices of project management offices for supporting new product development in high-tech companies

The article, through presenting a company's project management office (PMO), argues about practices a PMO must establish for supporting new product development (NPD) in high-technology companies. A holistic case-study was performed where data gathered comes from interviews, direct and participant observation, and document analysis. The practices identified differ from the current literature about the PMO functions. The whole set of functions performed by the described PMO responds to specific processes an NPD project asks for. It begins monitoring, analysing, and systematising product requirements to develop project schedules. During project execution, it supports configuration management through engineering change management. When prototyping, it carries on provisions of the necessary materials and subcontracted processes for assembling and testing. These PMO functions are compared to the current PMO literature. It is suggested that the functions undertaken by the PMO can enhance the theoretical options for structuring PMOs in NPD-based companies avoiding mimicry dysfunctions.

Indicators on firm level innovation activities from web scraped data

This article presents data on companies' innovative behavior measured at the firm-level based on web scraped firm-level data derived from medium-high and high-technology companies in the European Union and the United Kingdom. The data are retrieved from individual company websites and contains in total data on 96,921 companies. The data provide information on various aspects of innovation, most significantly the research and development orientation of the company at the company and product level, the company’s collaborative activities, company’s products, and use of standards. In addition to the web scraped data, the dataset aggregates a variety firm-level indicators including patenting activities. In total, the dataset includes 28 variables with unique identifiers which enables connecting to other databases such as financial data.

Perfil del sector de alta tecnología en México: Una aproximación a la realidad

This article is the result of an exploratory research with the purpose of elucidating the profile of High Technology (TA) companies in Mexico, in relation to the processes of technological research and development, investment and cooperation. The information was obtained through a digital questionnaire that was sent to the companies via the internet. 112 companies from the Aerospace, Automotive, Manufacturing and IT sectors from seven states that have at least five sectors specialized in High Technology participated; Baja California, Chihuahua, the State of Mexico, Jalisco, Nuevo León, Puebla and Querétaro. Descriptive statistics techniques were used to process the data. One of the possibly known realities is that national companies are located in TA because of the company's line of work or activity, and not because of obtaining results as part of an intense Technological Research and Development process (TRD). These findings are a route for reflection and design of strategies that link various actors to jointly provide solutions: industry, society, academia, and government contribute to position México in the international framework of the knowledge economy and the achievement of better business economic results from the consequences obtained from innovation activities.

IMPACT OF TECHNOLOGY INVESTMENT ON FIRM’S PRODUCTION EFFICIENCY FACTOR IN MANUFACTURING

The goal of this paper is to investigate the impact of technology investments on production efficiency in manufacturing companies and how different these relationships are for low-technology and high-technology companies. The empirical part was based on the analysis of 2,848 large, small and medium-sized Czech companies by using Bayesian networks (BNs). The results show that technological investments have the greatest positive impact on the growth of labour productivity and on a decline in labour intensity in low technology enterprises. The technological investments have a positive impact on labour productivity growth in high-technology enterprises, but at the same time, the technological investments have an impact on the increase of labour intensity. On the contrary, the influence of investment growth was insignificant on the indicators of material and services intensity. Technologically intensive investments have a different impact on small, mediumsized and on large enterprises. The reaction of large companies depends on the category of technology intensity in contrast to small and medium-size enterprises.

The effect of exploitative leadership on knowledge hiding: a conservation of resources perspective

PurposeDrawing on conservation of resources (COR) theory, this study aims to explore the influencing mechanism of exploitative leadership on knowledge hiding. Specifically, this study focuses on the mediating role of psychological distress and the moderating role of hostile attribution bias in affecting the mediation.Design/methodology/approachData were collected from 324 employees of a high-technology company in China by a three-wave questionnaire survey. Hierarchical regression analysis and bootstrapping approach were employed to test hypotheses.FindingsThis study found that exploitative leadership was positively related to knowledge hiding and that psychological distress mediated this relationship. Moreover, the results revealed that the positive relationship between exploitative leadership and psychological distress and the indirect effect of exploitative leadership on knowledge hiding via psychological distress were stronger when hostile attribution was high rather than low.Practical implicationsThe findings of this study offer guidance for managers to better undermine the negative effects of exploitative leadership.Originality/valueFirst, this study extends the literature on exploitative leadership by verifying the positive effect of exploitative leadership on knowledge hiding. Second, this study enriches one’s understanding of the “black box” underlying the link between exploitative leadership and its consequences by demonstrating the mediating role of psychological distress. Third, by verifying the moderating role of hostile attribution bias, this study provides insights into the boundary conditions of the impact of exploitative leadership.

Deep Learning Systems: Algorithms, Compilers, and Processors for Large-Scale Production

This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing. Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications. Therefore, it is imperative to codesign algorithms, compilers, and hardware to accelerate advances in this field with holistic system-level and algorithm solutions that improve performance, power, and efficiency. Advancing DL systems generally involves three types of engineers: (1) data scientists that utilize and develop DL algorithms in partnership with domain experts, such as medical, economic, or climate scientists; (2) hardware designers that develop specialized hardware to accelerate the components in the DL models; and (3) performance and compiler engineers that optimize software to run more efficiently on a given hardware. Hardware engineers should be aware of the characteristics and components of production and academic models likely to be adopted by industry to guide design decisions impacting future hardware. Data scientists should be aware of deployment platform constraints when designing models. Performance engineers should support optimizations across diverse models, libraries, and hardware targets. The purpose of this book is to provide a solid understanding of (1) the design, training, and applications of DL algorithms in industry; (2) the compiler techniques to map deep learning code to hardware targets; and (3) the critical hardware features that accelerate DL systems. This book aims to facilitate co-innovation for the advancement of DL systems. It is written for engineers working in one or more of these areas who seek to understand the entire system stack in order to better collaborate with engineers working in other parts of the system stack. The book details advancements and adoption of DL models in industry, explains the training and deployment process, describes the essential hardware architectural features needed for today's and future models, and details advances in DL compilers to efficiently execute algorithms across various hardware targets. Unique in this book is the holistic exposition of the entire DL system stack, the emphasis on commercial applications, and the practical techniques to design models and accelerate their performance. The author is fortunate to work with hardware, software, data scientist, and research teams across many high-technology companies with hyperscale data centers. These companies employ many of the examples and methods provided throughout the book.

Balancing the Halo

Medical device manufacturers and other high-technology companies increasingly incorporate algorithmic data surveillance in next-generation medical wearables. These devices, including hearing aids, leverage patient data created through human-computer interaction to not only power devices but also increase corporate profits. Although data protection laws establish privacy requirements for personal information collection and use, these companies continue to use patients’ personal information with little notice or education, significantly curtailing the agency of wearers. We explore the complex ecology of the Starkey Halo smart hearing aid, focusing on the opacity of its algorithmic functionality and examining patient education materials for disclosures of data surveillance. We contextualize these findings within privacy law in the United States and European Union that are relevant to algorithmic surveillance and recommend specific steps to enhance wearer agency through informed decision-making.