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The successful implementation and continuous development of sustainable corporate-level solutions is a challenge. These are endeavours in which social, environmental, and financial aspects must be weighed against each other. They can prove difficult to handle and, in some cases, almost unrealistic. Concepts such as green controlling, IT, and manufacturing look promising and are constantly evolving. This paper aims to achieve a better understanding of the field of corporate sustainability (CS). It will evaluate the hypothesis by which Corporate Sustainability thrives, via being efficient, increasing the performance, and raising the value of the input of the enterprises to the resources used. In fact, Corporate Sustainability on the surface could seem to contradict the idea, which supports the understanding that it encourages the reduction of the heavy reliance on the use of natural resources, the overall environmental impact, and above all, their protection. To understand how the contradictory notion of CS came about, in this part of the paper, the emphasis is placed on providing useful insight to this regard. The first part of this paper summarizes various definitions, organizational theories, and measures used for CS and its derivatives like green controlling, IT, and manufacturing. Second, a case study is given that combines the aforementioned sustainability models. In addition to evaluating the hypothesis, the overarching objective of this paper is to demonstrate the use of green controlling, IT, and manufacturing in the corporate sector. Furthermore, this paper outlines the current challenges and possible directions for CS in the future.
This publication is intended to present the current state of research on the rebound effect. First, a systematic literature review is carried out to outline (current) scientific models and theories. Research Question 1 follows with a mathematical introduction of the rebound effect, which shows the interdependence of consumer behaviour, technological progress, and interwoven effects for both. Thereupon, the research field is analysed for gaps and limitations by a systematic literature review. To ensure quantitative and qualitative results, a review protocol is used that integrates two different stages and covers all relevant publications released between 2000 and 2019. Accordingly, 392 publications were identified that deal with the rebound effect. These papers were reviewed to obtain relevant information on the two research questions. The literature review shows that research on the rebound effect is not yet comprehensive and focuses mainly on the effect itself rather than solutions to avoid it. Research Question 2 finds that the main gap, and thus the limitations, is that not much research has been published on the actual avoidance of the rebound effect yet. This is a major limitation for practical application by decision-makers and politicians. Therefore, a theoretical analysis was carried out to identify potential theories and ideas to avoid the rebound effect. The most obvious idea to solve this problem is the theory of a Steady-State Economy (SSE), which has been described and reviewed.
Rapid development of virtual and data acquisition technology makes Digital Twin Technology (DT) one of the fundamental areas of research, while DT is one of the most promissory developments for the achievement of Industry 4.0. 48% percent of organisations implementing the Internet of Things are already using DT or plan to use DT in 2020. The global market for DT is expected to grow by 38 percent annually, reaching USD16 billion by 2023. In addition, the number of participating organisations using digital twins is expected to triple by 2022. DTs are characterised by the integration between physical and virtual spaces. The driving idea for DT is to develop, test and build our devices in a virtual environment. The objective of this paper is to study the impact of DT in the automotive industry on the new marketing logic. This paper outlines the current challenges and possible directions for the future DT in marketing. This paper will be helpful for managers in the industry to use the advantages and potentials of DT.
This paper uses a quantitative analysis to examine the interdependence and impact of resource rents on socio-economic development from 2002 to 2017. Nigeria and Norway have been chosen as reference countries due to their abundance of natural resources by similar economic performance, while the ranking in the Human Development Index differs dramatically. As the Human Development Index provides insight into a country’s cultural and socio-economic characteristics and development in addition to economic indicators, it allows a comparison of the two countries. The hypothesis presented and discussed in this paper was researched before. A qualitative research approach was used in the author’s master’s thesis “The Human Development Index (HDI) as a Reflection of Resource Abundance (using Nigeria and Norway as a case study)” in 2018. The management of scarce resources is an important aspect in the development of modern countries and those on the threshold of becoming industrialised nations. The effects of a mistaken resource management are not only of a purely economic nature but also of a social and socio-economic nature. In order to present a partial aspect of these dependencies and influences this paper uses a quantitative analysis to examine the interdependence and impact of resource rents on socio-economic development from 2002 to 2017. Nigeria and Norway have been chosen as reference countries due to their abundance of natural resources by similar economic performance, while the ranking in the Human Development Index differs significantly. As the Human Development Index provides insight into a country’s cultural and socio-economic characteristics and development in addition to economic indicators, it allows a comparison of the two countries. This paper found out in a holistic perspective that (not or poorly managed) resource wealth in itself has a negative impact on socio-economic development and significantly reduces the productivity of the citizens of a state. This is expressed in particular for the years 2002 till 2017 in a negative correlation of GDP per capita and HDI value with the share respectively the size of resources in the GDP of a country.
The following article deals with the basic principles of intercultural management and possible improvements in terms of cultural, ethnic and gender diversification. The results are exemplarily applied to a bank located in Germany. The aim of this paper is to find out to what extent intercultural management could improve the productivity of Relatos-Bank in dealing with foreign employees or employees with a different cultural background. To achieve this goal, the authors con-duct a literature research. The main sources of information are books, journal articles and internet sources. It becomes clear that especially the different perceptions of different generations have a potential for conflict, which can be counteracted by applying presented scientific models. Equalizing the salaries of female and male employees and equalizing the rights and distribution of power could also be the key to becoming an open-minded, dynamic and fair organization that is pre-pared for the rapidly changing environment in which it operates.
The presented paper gives an overview of the most important and most common theories and concepts from the economic field of organisational change and is also enriched with quantitative publication data, which underlines the relevance of the topic. In particular, the topic presented is interwoven in an interdisciplinary way with economic psychological models, which are underpinned within the models with content from leading scholars in the field. The pace of change in companies is accelerating, as is technological change in our society. Adaptations of the corporate structure, but also of management techniques and tasks, are therefore indispensable. This includes not only the right approaches to employee motivation, but also the correct use of intrinsic and extrinsic motivational factors. Based on the hypothesis put forward by the scientist and researcher Rollinson in his book “Organisational behaviour and analysis” that managers believe motivational resources are available at all times, socio-economic and economic psychological theories are contrasted here in order to critically examine this statement. In addition, a fictitious company was created as a model for this work in order to illustrate the effects of motivational deficits in practice. In this context, the theories presented are applied to concrete problems within the model and conclusions are drawn about their influence and applicability. This led to the conclusion that motivation is a very individual challenge for each employee, which requires adapted and personalised approaches. On the other hand, the recommendations for action for supervisors in the case of motivation deficits also cannot be answered in a blanket manner, but can only be solved with the help of professional, expert-supported processing due to the economic-psychological realities of motivation. Identifying, analysing and remedying individual employee motivation deficits is, according to the authors, a problem and a challenge of great importance, especially in the context of rapidly changing ecosystems in modern companies, as motivation also influences other factors such as individual productivity. The authors therefore conclude that good motivation through the individual and customised promotion and further training of employees is an important point for achieving important corporate goals in order to remain competitive on the one hand and to create a productive and pleasant working environment on the other.
Today’s society is undergoing a paradigm shift driven by the megatrend of sustainability. This undeniably affects all areas of Western life. This paper aims to find out how the luxury industry is dealing with this change and what adjustments are made by the companies. For this purpose, interviews were conducted with managers from the luxury industry, in which they were asked about specific measures taken by their companies as well as trends in the industry. In a subsequent evaluation, the trends in the luxury industry were summarized for the areas of ecological, social, and economic sustainability. It was found that the area of environmental sustainability is significantly more focused than the other sub-areas. Furthermore, the need for a customer survey to validate the industry-based measures was identified.
By developing innovative solutions to social and environmental problems, sustainable ventures carry greatpotential. Entrepreneurship which focuses especially on new venture creation can be developed through education anduniversities, in particular, are called upon to provide an impetus for social change. But social innovations are associatedwith certain hurdles, which are related to the multi-dimensionality, i.e. the tension between creating social,environmental and economic value and dealing with a multiplicity of stakeholders. The already complex field ofentrepreneurship education has to face these challenges. This paper, therefore, aims to identify starting points for theintegration of sustainability into entrepreneurship education. To pursue this goal experiences from three differentproject initiatives between the partner universities: Lapland University of Applied Sciences, FH Aachen University ofApplied Sciences and Turiba University are reflected and findings are systematically condensed into recommendationsfor education on sustainable entrepreneurship.
Prioritization is an essential task within requirements engineering to cope with complexity and to establish focus properly. The 3rd Workshop on Requirements Prioritization for customer oriented Software Development (RePriCo’12) focused on requirements prioritization and adjacent themes in the context of customer oriented development of bespoke and standard software. Five submissions have been accepted for the proceedings and for presentation. The report summarizes and points out key findings.
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.
Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.
Eye movement modelling examples (EMME) are instructional videos that display a
teacher’s eye movements as “gaze cursor” (e.g. a moving dot) superimposed on the
learning task. This study investigated if previous findings on the beneficial effects of EMME would extend to online lecture videos and compared the effects of displaying the teacher’s gaze cursor with displaying the more traditional mouse cursor as a tool to guide learners’ attention. Novices (N = 124) studied a pre-recorded video lecture on how to model business processes in a 2 (mouse cursor absent/present) × 2 (gaze cursor absent/present) between-subjects design. Unexpectedly, we did not find significant effects of the presence of gaze or mouse cursors on mental effort and learning. However, participants who watched videos with the gaze cursor found it easier to follow the teacher. Overall, participants responded positively to the gaze cursor, especially when the mouse cursor was not displayed in the video.
We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts.
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
This Research Briefing, issued in July 2010, concluded that:
- Small and medium-sized enterprises (SMEs) in Europe have long called for a matching legal form valid across the EU (similar to that of the European company (SE) for large firms)
- The main benefits would be the availability of uniform Europe-wide company structures, significant cost reductions for businesses and further integration of the internal market
- Given the differing national views regarding the concrete features of the new legal form there is currently no sign of an agreement being reached at the European level in the short term; however, it is possible that progress will be made in negotiations during the year
- The key issues being discussed in depth are company formation, transnationality and employee participation rights in the new European private company (SPE).
Does stiffer electoral competition reduce political shirking? For a micro-analysis of this question, I construct a new data set spanning the years 2005 to 2012 covering biographical and political information about German Members of Parliament (MPs), including their attendance rates in voting sessions. For the parliament elected in 2009, I show that indeed opposition party MPs who expect to face a close race in their district show significantly and relevantly lower absence rates in parliament beforehand. MPs of governing parties seem not to react significantly to electoral competition. These results are confirmed by an analysis of the parliament elected in 2005, by several robustness checks, and also by employing an instrumental variable strategy exploiting convenient peculiarities of the German electoral system. The study also shows how MPs elected via party lists react to different levels of electoral competition.
Divided government is often thought of as causing legislative deadlock. I investigate the link between divided government and economic reforms using a novel data set on welfare reforms in US states between 1978 and 2010. Panel data regressions show that, under divided government, a US state is around 25% more likely to adopt a welfare reform than under unified government. Several robustness checks confirm this counter-intuitive finding. Case study evidence suggests an explanation based on policy competition between governor, senate, and house.
This paper investigates the extent to which corporate governance affects the cost of debt and equity capital of German exchange-listed companies. I examine corporate governance along three dimensions: financial information quality, ownership structure and board structure. The results suggest that firms with high levels of financial transparency and bonus compensations face lower cost of equity. In addition, block ownership is negatively related to firms' cost of equity when the blockholders are other firms, managers or founding-family members. Consistent with the conjecture that agency costs increase with firm size, I find significant cost of debt effects only in the largest German companies. Here, the creditors demand lower cost of debt from firms with block ownerships held by corporations or banks. My findings demonstrate that a uniform set of governance attributes is unlikely to satisfy suppliers of debt and equity capital equally.
With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.
Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.
We analyze the trading behavior of individual investors in option-like securities, namely bankissued warrants, and thus expand the growing literature of investors behavior to a new kind of securities. A unique data set from a large German discount broker gives us the opportunity to analyze the trading behavior of 1,454 investors, making 89,958 transactions in 6,724 warrants on 397 underlyings. In different logit regression, we make use of the facts that investors can speculate on rising and falling prices of the underlying with call and put warrants and that we also have information about the stock portfolios of the investors. We report several facts about the trading behavior of individual investors in warrants that are consistent with the literature on the behavior of individual investors in the stock market. The warrant investors buy calls and sell puts if the price of the underlying has decreased over the past trading days and they sell calls and buy puts if the price of the underlying has increased. That means, the investors follow negative feedback trading strategies in all four trading categories observed. In addition, we find strong evidence for the disposition effect for call as well as put warrants, which is reversed in December. The trading behavior is also influenced if the underlying reaches some exceptionally prices, e.g. highs, lows or the strike price. We show that hedging, as one natural candidate to buy puts, does not play an important role in the market for bank-issued warrants.
Knowledge-based productivity in “low-tech” industries: evidence from firms in developing countries
(2014)
Using firm-level data from five developing countries—Brazil, Ecuador, South Africa, Tanzania, and Bangladesh—and three industries—food processing, textiles, and the garments and leather products—this article examines the importance of various sources of knowledge for explaining productivity and formally tests whether sector- or country-specific characteristics dominate these relationships. Knowledge sources driving productivity appear mainly sector specific. Also differences in the level of development affect the effectiveness of knowledge sources. In the food processing sector, firms with higher educated managers are more productive, and in least-developed countries, additionally those with technology licenses and imported machinery and equipment. In the capital-intensive textiles sector, productivity is higher in firms that conduct R&D. In the garments and leather products sector, higher education of the managers, licensing, and R&D raise productivity.
The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantifiedin a straightforward way by the probability that the decision of the test is correct. However, the quantification of the precision of a statistical test is not at all evident. Thereforethe paper presents and discusses several approaches. Moreover the distinction of “nullhypothesis” and “alternative hypothesis” is not necessary any longer.
Next Generation Access Networks: Why is there a higher risk of investment and how to deal with it?
(2009)
Die Garantie im Kaufrecht
(1995)