SQ mGov: A Comprehensive Service-Quality Paradigm for Mobile Government
Why this work is in the frame
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Bibliographic record
Abstract
AbstractService quality of Mobile Government (mGov) is an important concept; however, to date, there has been relatively little work conducted in this emerging area. Based on an empirical study conducted among 1404 users of mGov in Mumbai, India, this study conceptualizes and identifies four service-quality dimensions—connectivity, interactivity, understandability, and authenticity—as the formative constructs of mGov service quality, and 16 measuring items to evaluate those dimensions as the reflective indicators.Keywords: mGoveGovcitizenservice qualityconsumer behavior Additional informationNotes on contributorsMahmud Akhter ShareefMahmud Akhter Shareef is an associate professor of School of Business, North South University, Bangladesh. He was a visiting faculty in DeGroote School of Business, McMaster University, Canada, during his post doctorate research. He has done his PhD in Business Administration from Sprott School of Business, Carleton University, Canada. He received his graduate degree from both the Institute of Business Administration, University of Dhaka, Bangladesh in Business Administration and Carleton University, Ottawa, Canada in Civil Engineering. He has published more than 50 papers addressing consumers adoption behavior and quality issues of e-commerce and e-government in different leading journals of IS and marketing.Yogesh K. DwivediYogesh K. Dwivedi is a professor in the School of Management, Swansea University, Wales, UK. He obtained his PhD and MSc in Information Systems from Brunel University, UK. He has co-authored several papers which have appeared in international referred journals such as CACM, DATA BASE, EJIS, ISJ, ISF, JCIS, JIT, JORS, and IMDS. He is Associate Editor of EJIS, Assistant Editor of TGPPP, Managing Editor of JECR and member of the editorial board/review board of several journals. He is a member of the AIS and IFIP WG8.6.Teta StamatiTeta Stamati obtained her degree in Computer Science from the National and Kapodistrian University of Athens, Greece. She also holds an MPhil in enterprise modeling techniques from the University of Manchester Institute of Science and Technology (UMIST) in the UK, an MBA Degree from Lancaster University Management School in the UK, and a PhD from the National and Kapodistrian University of Athens, Greece. Currently she is adjunct faculty member at University of Athens. Greece. She has extensive experience in top management positions in leading ICT companies of the Greek and European private sector.Michael D. WilliamsMichael D. Williams is a professor in the School of Management at Swansea University in the UK. He holds a BSc from the CNAA, an MEd from the University of Cambridge, and a PhD from the University of Sheffield. Prior to entering academia, Professor Williams spent twelve years developing and implementing ICT systems in both public and private sectors. He is the author of numerous fully refereed and invited papers within the ICT domain, has editorial board membership of a number of academic journals, and has obtained external research funding from sources including the European Union, the Nuffield Foundation, and the Welsh Assembly Government.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it