Does Public Concern Affect the Greenhouse Gas Emissions of Oil and Gas Production, Through Logistics?

Today’s globalized world is well aware that the fossil fuel industry is the main contributor to greenhouse gas (GHG) emissions that cause global warming and climate change. Negative public opinion about the oil and gas industry is rising globally. A growing number of global citizens are adept at shifting public sentiment about oil and gas industry emissions, particularly in Logistics industry. In this context, oil and gas companies have begun to substantially invest in renewable energy sources in a bid to diversify their oil and gas product portfolios to mitigate climate change risks in line with Logistics industry. This energy transition is influenced by rising social concern about climate change. Energy transition is an environmental management system and its outcomes benefit dry zone agriculture and many other business sectors. In this research work, we used qualitative data obtained from real social surveys conducted by Yale University and Pew Research Center from 2013 to 2019 and the emissions data disclosed by oil and gas companies for the same time period, and we use Excel spreadsheets to give graphic and numeric outputs in a time-series analysis. The outcome of the analysis tells us the relationship between the social concern about climate change and emissions reduction and the environmental performance of oil and gas companies. Our analysis shows that public concern about climate change is always high in Europe compared to the United States, but it has been increasing steadily on both continents, in Europe from 54% in 2015 to 79% in 2019 and in the United States from 40% in 2013 to 69% in 2019. Our graphical analysis reveals social concern has had a real impact on climate change, leading to a reduction of over ten million tons of emissions annually in 2013–2019 on both sides of the Atlantic, while meeting growing energy demand particularly in the United States.  

Critical Factors of Software Quality Management (SQM)

The importance of managing quality in developing software systems is well documented. Existing literature presents attributes of good quality management practices in building software systems on time, within budget, and satisfying customer needs. However, most of the current findings on Software Quality Management (SQM) are case-based and company-specific, and may not be generalizable across all software developing organizations. Furthermore, the relationships examined in past research may be incomplete and therefore fail to identify differing dimensions critical for SQM. Against this backdrop, our research provides a synthesis of existing literature by identifying six critical factors of SQM in software developing organizations. An instrument that can be used to measure critical factors of SQM is constructed. Validity and reliability of the instrument is established using a combination of exhaustive literature review, pre-pilot testing a preliminary version of the instrument among a group of academics, and pilot testing revised versions of the instrument among a group of IS professionals who are affected by software quality. An instrument such as the one proposed in this research could be used by senior IS managers to assess the effectiveness of SQM practices in developing quality software. Researchers on the other hand could use the instrument to better understand SQM practices, and build theories and models to manage software quality effectively

A comprehensive study of the short-term variability of the migrating diurnal tide in the mesosphere and lower thermosphere.

Our ability to understand and predict space weather has become vital due to its significant societal impacts on communication, transportation, and national defense. One of the most exciting discoveries in the last decade has been the realization that tropospheric weather can strongly influence space weather. It is now recognized that the atmospheric waves (gravity waves, atmospheric tides, and planetary waves) play a key role in coupling the lower and upper atmosphere. The focus of this dissertation is to study atmospheric tides. While the climatology of tides has been extensively studied, little is known about the tidal weather (tidal variabilit

Information Systems Outsourcing: Linking Transaction Cost and Institutional Theories

In this article, we apply transaction cost theory (TCT) and institutional theory to the realm of IS outsourcing. TCT posits that firm\u27s outsourcing governance is influenced by transaction cost factors, namely, bounded rationality, opportunism, and risk. Institutional theory, on the other hand, has been advocated to explain non-choice behavior of organizations in the context of competitors, norms, and professional associations. Although TCT has been used extensively in the extant literature to study outsourcing arrangements, we argue that as IS outsourcing practices propagate in organizational fields, TCT explanations will take a back seat to institutional explanations. We appropriate the transaction cost framework to the IS outsourcing setting and consider when and how firm\u27s decision to adopt outsourcing and corresponding ex-ante screening and ex-post monitoring of the vendor will be influenced by mimetic, normative, and coercive institutional pressures. More specifically, we argue that greater the density and rate of adoption in outsourcing during innovation diffusion and stability stages, the greater the possibility that transaction cost factors will be replaced by institutional factors in explaining firms\u27 governance structures (decision to adopt outsourcing, and corresponding screening and monitoring). Conversely, we posit that when the institutional pressures are relatively weak, TCT better explains the intricacies of IS outsourcing arrangements. In conclusion, future research directions and managerial implications of the institutional environment on IS outsourcing governance are discussed

Software Application Outsourcing Contracts: An Agency Theory Perspective

Scholars have proposed agency, game, resource-dependency, and transaction cost theories as a means to study outsourcing. Although risks faced by outsourcing firms and developers (i.e., vendors) and corresponding agency costs have been identified, key agency constructs (e.g., firm competence, risk-neutrality of the developer) and their linkage to outsourcing practice (e.g., monitoring, screening) have not been extensively studied. In this research, we extend the classical agency theory by examining the impact of risk orientation of the outsourcing parties, application features, multi-period attributes and environmental factors on monitoring, bonding, compensation, screening, and signaling. By developing the agency framework, we set the stage for future empirical testing of key outsourcing constructs and their linkages

Computer-Mediated Group Support, Anonymity and Software Inspection Process

While considerable research in both software inspection and anonymity in Group Decision Support Systems (GDSS) exists individually, anonymity within the context of software inspection has not been explored. Anonymity becomes an important issue as researchers and practitioners advocate the use of computer- mediated inspection over traditional manual-based ones. Moreover, the emergence of new paradigms such as distributed and asynchronous environments for inspection only add to the importance of understanding the effects of anonymity on inspection outcomes. This research examines and proposes possible influences of group member anonymity on the outcome of computer-mediated software inspection

Group Decision Support forSoftware Requirements Analysis

The importance of Requirements Analysis (RA) in building quality software systems is well documented. However, the involvement of various individuals in RA including users and developers creates numerous communication difficulties in correctly identifying user requirements. The purpose of this research is to formalize the stages of RA and identify methodologies appropriate for each stage, incorporating components of group decision support systems (GDSS) that exploit the group dynamics in facilitating and improving the process. We develop a prototype of this GDSS and test its impact on the quality of R

Spatial Variability of Cadmium and Lead in Surface Soils in-relation to Landuse and Topography

Accumulation of trace elements in soils has become an environmental concern. Understanding spatial variability of trace elements in relation to point and non-point sources is important to identify threats and monitoring mechanisms. Objectives of this study were to explore the spatial variability of cadmium (Cd) and lead (Pb) in relation to the land-use and topography. One hundred and thirty seven surface soil (0-15 cm) samples were collected from a tropical Ultisol soil scape in up-and mid-country in wet zone in Sri Lanka, representing tea, forest, and urban land uses. Total Cd and Pb concentrations were determined by digesting the soils using aqua regia (Trace-metal grade) and analysed using Graphite Furnace Atomic Absorption Spectrophotometer, following USEPA method 7010.Extractable concentrations of Cd and Pb were determined using Mehlich 3 extraction. Soil pH, electrical conductivity, cation exchange capacity, available P, total P, amorphous Fe, total Fe and Mn were determined using standard methods. Total and Mehlich 3 concentrations of trace elements showed positively skewed data distributions. Across all the land uses, the total Cd and Pb concentrations ranged from 0.05 to 0.40 mg kg-1 (median: Tea=16, Urban=13, Forest=19) and 3 to 37 mgkg-1 (median: Tea=0.13, Urban=0.14, Forest=0.16) respectively. Mehlich 3 Cd and Pb concentrations were low and ranged from 0.01 to 0.62 mgkg-1and 1 to 26 mgkg-1, respectively. Potential bioavailability of Cd in tea, urban and forest land uses was 40%, 32% and 32% respectively, meanwhile for Pb it was 40%, 60% and 40% respectively. Regression analysis explained that the relationship of total Pb and Mehlich 3 extractable Pb concentrations with elevation was significant (p<0.05); However, only about 4-7% of variation of them was explained by elevation. Cd concentration was not significantly related to elevation. Variability of concentrations of Cd and Pb were not related to land use. Soil associations were also not related to spatial variability of total concentrations of Cd and Pb in soils. Spatial variability of total concentrations of Cd and Pb will be presented with maps including land use, soil association and elevation distribution.Keywords: Potential bioavailability, Spatial variability, Topography, Trace element

Enhancing Analysts’ Mental Models for Improving Requirements Elicitation: A Two-stage Theoretical Framework and Empirical Results

Research has extensively documented the importance of accurate system requirements in avoiding project delays, cost overruns, and system malfunctions. Requirement elicitation (RE) is a critical step in determining system requirements. While much research on RE has emerged, a deeper understanding of three aspects could help significantly improve RE: 1) insights about the role and impacts of support tools in the RE process, 2) the impact of using support tools in multiple stages of the RE process, and 3) a clear focus on the multiplicity of perspectives in assessing RE outcomes. To understand how using support tools could improve RE, we rely on the theoretical lens of mental models (MM) to develop a dynamic conceptual model and argue that analysts form mental models (MMs) of the system during RE and these MMs impact their outcome performance. We posit that one can enhance analysts’ MMs by using a knowledge-based repository (KBR) of components and services embodying domain knowledge specific to the target application during two key stages of RE, which results in improved RE outcomes. We measured the RE outcomes from user and analyst perspectives. The knowledge-based component repository we used in this research (which we developed in collaboration with a multi-national company) focused on insurance claim processing. The repository served as the support tool in RE in a multi-period lab experiment with multiple teams of analysts. The results supported the conceptualized model and showed the significant impacts of such tools in supporting analysts and their performance outcomes at two stages of RE. This work makes multiple contributions: it offers a theoretical framework for understanding and enhancing the RE process, develops measures for analysts’ mental models and RE performance outcomes, and shows the process by which one can improve analysts’ RE performance through access to a KBR of components at two key stages of the RE process