An empirical examination of the strategic decision-making process:the relationship between context, process, and outcomes

Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.

Abusive supervision and contextual performance:The mediating role of emotional exhaustion and the moderating role of work unit structure

This study examined the processes linking abusive supervision to employee contextual performance by focusing on the mediating influence of emotional exhaustion and the moderating influence of work unit structure. Data were obtained from 285 subordinate-supervisor dyads from three manufacturing companies in north-eastern China. The results revealed that: (i) emotional exhaustion mediated the relationships between abusive supervision and the contextual performance dimensions of interpersonal facilitation and job dedication; and (ii) work unit structure moderated these relationships such that the relationships were stronger in mechanistic than in organic work unit structures. © 2008 Blackwell Publishing Ltd.

Contextual semantics for sentiment analysis of Twitter

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.

Adapting sentiment lexicons using contextual semantics for sentiment analysis of Twitter

Sentiment lexicons for sentiment analysis offer a simple, yet effective way to obtain the prior sentiment information of opinionated words in texts. However, words' sentiment orientations and strengths often change throughout various contexts in which the words appear. In this paper, we propose a lexicon adaptation approach that uses the contextual semantics of words to capture their contexts in tweet messages and update their prior sentiment orientations and/or strengths accordingly. We evaluate our approach on one state-of-the-art sentiment lexicon using three different Twitter datasets. Results show that the sentiment lexicons adapted by our approach outperform the original lexicon in accuracy and F-measure in two datasets, but give similar accuracy and slightly lower F-measure in one dataset.

Adapting sentiment lexicons using contextual semantics for sentiment analysis of twitter

Sentiment lexicons for sentiment analysis offer a simple, yet effective way to obtain the prior sentiment information of opinionated words in texts. However, words’ sentiment orientations and strengths often change throughout various contexts in which the words appear. In this paper, we propose a lexicon adaptation approach that uses the contextual semantics of words to capture their contexts in tweet messages and update their prior sentiment orientations and/or strengths accordingly. We evaluate our approach on one state-of-the-art sentiment lexicon using three different Twitter datasets. Results show that the sentiment lexicons adapted by our approach outperform the original lexicon in accuracy and F-measure in two datasets, but give similar accuracy and slightly lower F-measure in one dataset.

SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter

Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words' sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach that takes into account the contextual and conceptual semantics of words when calculating their sentiment orientation and strength in Twitter. We evaluate our approach on three Twitter datasets using three different sentiment lexicons. Results show that our approach significantly outperforms two lexicon baselines. Results are competitive but inconclusive when comparing to state-of-art SentiStrength, and vary from one dataset to another. SentiCircle outperforms SentiStrength in accuracy on average, but falls marginally behind in F-measure. © 2014 Springer International Publishing.

Block, L. (2011). ‘From politics to policing: the rationality gap in EU Council policy- making’

Book review: L Block. (2011). From Politics to Policing: The Rationality Gap in EU Council Policy-Making The Hague: Eleven International Publishing. ISBN: 978-94-9094-737-8, 361 pages.

Tax morale and tax evasion: Social preferences and bounded rationality

We study a family of models of tax evasion, where a flat-rate tax finances only the provision of public goods, neglecting audits and wage differences. We focus on the comparison of two modeling approaches. The first is based on optimizing agents, who are endowed with social preferences, their utility being the sum of private consumption and moral utility. The second approach involves agents acting according to simple heuristics. We find that while we encounter the traditionally shaped Laffer-curve in the optimizing model, the heuristics models exhibit (linearly) increasing Laffercurves. This difference is related to a peculiar type of behavior emerging within the heuristics based approach: a number of agents lurk in a moral state of limbo, alternating between altruism and selfishness.

Adómorál és adócsalás - társadalmi preferenciák és korlátozott racionalitás = Tax morale and tax system: social preferences and bounded rationality

Az adócsalásnak egy olyan modellcsaládját vizsgáljuk, ahol az egykulcsos adó kizárólag a közjavakat finanszírozza. Két megközelítés összehasonlítására összpontosítunk. Az elsőben minden dolgozó jövedelme azonos, és ebből minden évben annyit vall be, amennyi maximalizálja a nála maradó jövedelemből fedezhető fogyasztás nyújtotta hasznosság és a jövedelembevallásból fakadó hasznosság összegét. A második hasznosság három tényező szorzata: a dolgozó exogén adómorálja, a környezetében előző évben megfigyelt átlagos jövedelembevallás és saját bevallásából fakadó endogén hasznossága. A második megközelítésben az ágensek egyszerű heurisztikus szabályok szerint cselekszenek. Míg az optimalizáló modellben hagyományos Laffer-görbékkel találkozunk, addig a heurisztikán alapuló modellekben (lineárisan) növekvő Laffer-görbék jönnek létre. E különbség oka, hogy a heurisztikán alapuló modellben egy sajátos viselkedésfajta jelentkezik: számos ágens ingatag helyzetbe kerül, amelyben altruizmus és önzés között ingadozik. ________ The authors study a family of models of tax evasion, where a flat-rate tax only finances the provision of public goods and audits and wage differences are ne-glected. The paper focuses on comparing two modelling approaches. The first is based on optimizing agents, endowed with social preferences, their utility being the sum of private consumption and moral utility. The second approach involves agents acting according to simple heuristics. While the traditionally shaped Laffer curves are encountered in the optimizing model, the heuristics models exhibit (linearly) increasing Laffer curves. This difference is related to a peculiar type of behaviour: within the agent-based approach lurk a number of agents in a moral state of limbo, alternating between altruism and selfishness.

A projektalapú szervezetek projektmarketing-tevékenységének sajátos kontextusa (Contextual features of project marketing activity of the project-based organisations)

Ez a tanulmány a projektvezetési szakirodalomban kialakult ismeretanyagot szem előtt tartva (noha tételesen nem hivatkozva arra) tárja fel azt a sajátos és tipikusnak nevezhető kontextust, amelyben a projektalapú szervezetek projektmarketing tevékenysége megnyilvánul. A tanulmány célja tehát nem magának a projektmarketingnek a kérdéskörére irányul, hanem elsősorban annak projektspecifikus kontextusára. Jellegét illetően a tanulmány spekulatív jellegű, vagyis lényegét tekintve nem empirikus kutatási eredményekből levont következtetésekre épül. _____ Traditional approach to project marketing focuses on process-related aspects of the marketing efforts of project- based organisations. This paper is different. Unlike to the traditional approach it highlights the decisive contextual features of project marketing, bearing in mind the typical project business from the point of view of project-based organisations. These features include: a) instead of physically existing products project-based organisations need to sell their ability to create the project outcome physically; b) the project outcome and the conditions of implementation are defined by the project client; c) project clients are involved in creating the project outcome; d) project implementation strategy applied in a client organisation may vary project by project. These determining contextual features shape to a great extent the actual competitive position of the project-based organisations which may vary project by project even in relation to the very same project client.

The conflict resolution behaviors of occupational therapy students as a function of the personality types, demographic characteristics and contextual factors

Interpersonal conflicts have the potential for detrimental consequences if not managed successfully. Understanding the factors that contribute to conflict resolution has implications for interpersonal relationships and the workplace. Researchers have suggested that personality plays an important and predictable role in conflict resolution behaviors (Chanin & Schneer, 1984; Kilmann & Thomas, 1975; Mills, Robey & Smith, 1985). However, other investigators have contended that contextual factors are important contributors in triggering the behavioral responses (Shoda & Mischel, 2000; Mischel & Shoda, 1995). The purpose of this study was to investigate the relationships among personality types, demographic characteristics and contextual factors on the conflict resolution behaviors reported by graduate occupational therapy students (n = 125). ^ The study design was correlational. The Myers Briggs Type Indicator (MBTI) and the Thomas-Kilmann (MODE) Instrument were used to establish the personality types and the context independent conflict resolution behaviors respectively. The effects of contextual factors of task vs. relationship and power were measured with the Conflict Case Scenarios Questionnaire (CCSQ). One-way ANOVA and linear regression procedures were used to test the relationships between personality types and demographic characteristics with the context independent conflict behaviors. Chi-Square procedures of the personality types by contextual conditions ascertained the effects of contexts in modifying the resolution modes. Descriptive statistics established a profile of the sample. ^ The results of the hypotheses tests revealed significant relationships between the personality types of feeling-thinking and sensing-intuition with the conflict resolution behaviors. The contextual attributes of task vs. relationship orientation and of peer vs. supervisor relationships were shown to modify the conflict behaviors. Furthermore, demographic characteristics of age, gender, GPA and educational background were shown to have an effect on the conflict resolution behaviors. The knowledge gained has implications for students' training, specifically understanding their styles and use of effective conflict resolution strategies. It also contributes to the knowledge on management approaches and interpersonal competencies and how this might facilitate the students' transition to the clinical role. ^

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

The relationship between cognitive ability, the big five, task and contextual performance: a meta-analysis

For years, researchers and human resources specialists have been searching for predictors of performance as well as for relevant performance dimensions (Barrick & Mount, 1991; Borman & Motowidlo, 1993; Campbell, 1990; Viswesvaran et al., 1996). In 1993, Borman and Motowidlo provided a framework by which traditional predictors such as cognitive ability and the Big Five personality factors predicted two different facets of performance: 1) task performance and 2) contextual performance. A meta-analysis was conducted to assess the validity of this model as well as that of other modified models. The relationships between predictors such as cognitive ability and personality variables and the two outcome variables were assessed. It was determined that even though the two facets of performance may be conceptually different, empirically they overlapped substantially (p= .75). Finally, results show that there is some evidence for cognitive ability as a predictor of both task and contextual performance and conscientiousness as a predictor of both task and contextual performance. The possible mediation of predictor-- criterion relationships was also assessed. The relationship between cognitive ability and contextual performance vanished when task performance was controlled.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Accounting for residential and non-residential environments to measure contextual effects on health behavior : the case of recreational walking behavior

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université Pierre et Marie Curie, Paris 06, Sorbonne Universités.