# Strategic Orientation and Effects of E-Administration: Findings from the Miles and Snow Framework

## Abstract

**:**

## 1. Introduction

## 2. Multidimensional Model of Measuring Effects of E-Administration

## 3. Strategic Orientation

**Hypothesis**

**1**

**(H1).**

**Hypothesis**

**2**

**(H2).**

**Hypothesis**

**3**

**(H3).**

**Hypothesis**

**4**

**(H4).**

## 4. Materials and Methods

## 5. Results

_{0}, ß

_{1}, ß

_{2}, ß

_{3}, ß

_{4}are the parameters to be estimated while u is the error term, and u has a normal distribution with the expected value of 0 and variance of ${\sigma}^{2}$.

_{0}, ß

_{1}, ß

_{2}, ß

_{3}, ß

_{4}are the parameters to be estimated while u is the error term, and u has a normal distribution with the expected value of 0 and variance of ${\sigma}^{2}$.

_{0}, ß

_{1}, ß

_{2}, ß

_{3}, ß

_{4}are the parameters to be estimated while u is the error term, and u has a normal distribution with the expected value of 0 and variance of ${\sigma}^{2}$.

## 6. Discussion and Conclusions

## Funding

## Conflicts of Interest

## References

- Adams, Dennis A., R. Ryan Nelson, and Peter A. Todd. 1992. Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly: Management Information Systems 16: 227–47. [Google Scholar] [CrossRef]
- Andrews, Rhys, George A. Boyne, and Richard M. Walker. 2006. Strategy content and organizational performance: An empirical analysis. Public Administration Review 66: 52–63. [Google Scholar] [CrossRef]
- Andrews, Rhys, George A. Boyne, Jennifer Law, and Richard M. Walker. 2009a. Strategy, structure and process in the public sector: A test of the miles and snow model. Public Administration 87: 732–49. [Google Scholar] [CrossRef]
- Andrews, Rhys, George A. Boyne, Jennifer Law, and Richard M. Walker. 2009b. Strategy formulation, strategy content and performance: An empirical analysis. Public Management Review 11: 1–22. [Google Scholar] [CrossRef]
- Andrews, Rhys, George A. Boyne, Jennifer Law, and Richard M. Walker. 2011. Strategy implementation and public service performance. Administration and Society 43: 643–71. [Google Scholar] [CrossRef][Green Version]
- Bearfield, Domonic A., and Ann O’M. Bowman. 2017. Can You Find It on the Web? An Assessment of Municipal E-Government Transparency. American Review of Public Administration 47: 172–88. [Google Scholar] [CrossRef]
- Bebenek, P. 2016. The Functioning of Outsourcing in the Polish Farms—Success and Failure in Outsourcing Projects. In 3rd International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM 2016, Book 2. Albena: Flamingo Grand Congress Center. [Google Scholar] [CrossRef]
- Bonsón, Enrique, Lourdes Torres, Sonia Royo, and Francisco Flores. 2012. Local e-government 2.0: Social media and corporate transparency in municipalities. Government Information Quarterly 29: 123–32. [Google Scholar] [CrossRef]
- Boyne, George A., and Richard M. Walker. 2004. Strategy content and public service organizations. Journal of Public Administration Research and Theory 14: 231–52. [Google Scholar] [CrossRef][Green Version]
- Boyne, George A., and Richard M. Walker. 2010. Strategic management and public service performance: The way ahead. Public Administration Review 70: s185–s192. [Google Scholar] [CrossRef]
- Bryson, John M., Fran Ackermann, and Colin Eden. 2007. Putting the resource-based view of strategy and distinctive competencies to work in public organizations. Public Administration Review 67: 702–17. [Google Scholar] [CrossRef]
- Chen, Yu-Che, Lung-Teng Hu, Kuan-Chiu Tseng, Wen-Jong Juang, and Chih-Kai Chang. 2019. Cross-boundary e-government systems: Determinants of performance. Government Information Quarterly 36: 449–59. [Google Scholar] [CrossRef]
- Cheon, Ohbet, and Seung-Ho An. 2017. Blowing in the wind: A study for Granger causality between managerial strategy and organizational performance. Public Management Review 19: 686–704. [Google Scholar] [CrossRef]
- Conant, Jeffrey S., Michael P. Mokwa, and P. Rajan Varadarajan. 1990. Strategic types, distinctive marketing competencies and organizational performance: A multiple measures-based study. Strategic Management Journal 11: 365–83. [Google Scholar] [CrossRef]
- Connolly, Regina, Frank Bannister, and Aideen Kearney. 2010. Government website service quality: A study of the Irish revenue online service. European Journal of Information Systems 19: 649–67. [Google Scholar] [CrossRef]
- Cumbie, Barry A., and Bandana Kar. 2016. A Study of Local Government Website Inclusiveness: The Gap Between E-government Concept and Practice. Information Technology for Development 22: 15–35. [Google Scholar] [CrossRef]
- Del Sordo, Carlotta, Rebecca L. Orelli, and Emanuele Padovani. 2017. Governing the public sector e-performance: The accounting practices in the digital age. In Decision Management: Concepts, Methodologies, Tools, and Applications. Hershey: IGI Global. [Google Scholar] [CrossRef]
- Desarbo, Wayne S., C. Anthony Di Benedetto, Michael Song, and Indrajit Sinha. 2005. Revisiting the miles and snow strategic framework: Uncovering interrelationships between strategic types, capabilities, environmental uncertainty, and firm performance. Strategic Management Journal 26: 47–74. [Google Scholar] [CrossRef]
- Dukić, Darko, Gordana Dukić, and Neven Bertović. 2017. Public administration employees’ readiness and acceptance of e-government: Findings from a Croatian survey. Information Development 33: 525–39. [Google Scholar] [CrossRef]
- Ejdys, Joanna. 2018. Building technology trust in ICT application at a university. International Journal of Emerging Markets. [Google Scholar] [CrossRef][Green Version]
- Flink, Carla M. 2015. Multidimensional Conflict and Organizational Performance. American Review of Public Administration 45: 182–200. [Google Scholar] [CrossRef]
- Florentina, Neamţu. 2013. Stakeholders, the determinant factors in development and operationalization of e-governance in Romania. Annals of the University of Oradea, Economic Science Series 22: 595–604. [Google Scholar]
- Gable, Guy G., Darshana Sedera, and Taizan Chan. 2008. Re-conceptualizing information system success: The IS-impact measurement model. Journal of the Association of Information Systems 9: 18. [Google Scholar] [CrossRef]
- Gatautis, Rimantas, Elena Vitkauskaitė, and Genadijus Kulvietis. 2009. Lithuanian eGovernment interoperability model. Engineering Economics 2: 38–48. [Google Scholar] [CrossRef]
- Gujarati, Damodar N. 2004. Basic Econometrics, 4th ed. New Delhi: Tata McGraw Hill. [Google Scholar] [CrossRef][Green Version]
- Harrow, Jenny. 2000. Public Management Reform: A Comparative Analysis. Long Range Planning 6: 881–84. [Google Scholar] [CrossRef]
- Hawrysz, Liliana, and Jolanta Maj. 2017. Identification of stakeholders of public interest organisations. Sustainability 9: 1609. [Google Scholar] [CrossRef][Green Version]
- Heeks, Richar. 2008. Benchmarking e-Government: Improving the national and international measurement, evaluation and comparison of e-Government. Evaluating Information Systems: Public and Private Sector 257. [Google Scholar] [CrossRef]
- Kassen, Maxat. 2014. Globalization of e-government: Open government as a global agenda; benefits, limitations and ways forward. Information Development 30: 51–58. [Google Scholar] [CrossRef]
- Kickert, Walter. 2007. The Study of Public Management in Europe and the US, The Study of Public Management in Europe and the US. New York: Routledge. [Google Scholar] [CrossRef]
- Kim, Na Yeon, and Frances S. Berry. 2018. Strategic stances and programme performance: Assessing outcomes of the US states’ delivery of the child support enforcement programme. Public Management Review 20: 545–62. [Google Scholar] [CrossRef]
- Korneta, Piotr. 2019. Critical success factors for Polish agricultural distributors. British Food Journal. [Google Scholar] [CrossRef]
- Kuk, George, and Marijn Janssen. 2013. Assembling infrastructures and business models for service design and innovation. Information Systems Journal 23: 445–69. [Google Scholar] [CrossRef]
- Lee, Choonwoo, Kyungmook Lee, and Johannes M. Pennings. 2001. Internal capabilities, external networks, and performance: A study on technology-based ventures. Strategic Management Journal 22: 615–40. [Google Scholar] [CrossRef][Green Version]
- Lee, Chung-pin, Kaiju Chang, and Frances Stokes Berry. 2011. Testing the Development and Diffusion of E-Government and E-Democracy: A Global Perspective. Public Administration Review 71: 444–54. [Google Scholar] [CrossRef]
- Lee-Geiller, Seulki, and Taejun David Lee. 2019. Using government websites to enhance democratic E-governance: A conceptual model for evaluation. Government Information Quarterly 36: 208–25. [Google Scholar] [CrossRef]
- Lim, Edwin KiaYang, Keryn Chalmers, and Dean Hanlon. 2018. The influence of business strategy on annual report readability. Journal of Accounting and Public Policy 37: 65–81. [Google Scholar] [CrossRef]
- Lips, Miriam. 2013. E-Government is dead: Long live Public Administration 2.0. ICT, Public Administration and Democracy in the Coming Decade 17: 239–50. [Google Scholar] [CrossRef]
- Ma, Liang, and Yueping Zheng. 2018. Does e-government performance actually boost citizen use? Evidence from European countries. Public Management Review 20: 1513–32. [Google Scholar] [CrossRef]
- Maj, J. 2015. Diversity management’s stakeholders and stakeholders management. Paper presented at the 9th International Management Conference, “Management and Innovation for Competitive Advantage”, Bucharest, Romania, November 5–6. [Google Scholar]
- Maj, Jolanta. 2018a. Embedding diversity in sustainability reporting. Sustainability 10: 2487. [Google Scholar] [CrossRef][Green Version]
- Maj, Jolanta. 2018b. Nature of non-financial information disclosed by Polish organisations. Paper presented at the 31st International Business Information Management Association Conference, IBIMA 2018: Innovation Management and Education Excellence through Vision 2020, Milan, Italy, April 25–26. [Google Scholar]
- Marwa, Simmy M., and Mohamed Zairi. 2009. In pursuit of performance-oriented civil service reforms (CSRs): A Kenyan perspective. Measuring Business Excellence 13: 34–43. [Google Scholar] [CrossRef]
- Meier, Kenneth J., Laurence J. O’Toole Jr., George A. Boyne, and Richard M. Walker. 2008. Strategic management and the performance of public organizations: Testing venerable ideas against recent theories. Journal of Public Administration Research and Theory. [Google Scholar] [CrossRef][Green Version]
- Meier, Kenneth J., Laurence J. O’Toole Jr., George A. Boyne, Richard M. Walker, and Rhys Andrews. 2010. Alignment and results: Testing the interaction effects of strategy, structure, and environment from miles and snow. Administration and Society. [Google Scholar] [CrossRef]
- Miles, Raymond E., Charles C. Snow, Alan D. Meyer, and Henry J. Coleman Jr. 1978. Organizational strategy, structure, and process. Academy of Management Review. [Google Scholar] [CrossRef]
- Nograšek, Janja, and Mirko Vintar. 2014. E-government and organisational transformation of government: Black box revisited? Government Information Quarterly. [Google Scholar] [CrossRef]
- Nograšek, Janja, and Mirko Vintar. 2015. Observing organisational transformation of the public sector in the e-government era. Transforming Government: People, Process and Policy. [Google Scholar] [CrossRef]
- Pasha, Obed Q., Theodore H. Poister, and Lauren H. Edwards. 2018. Mutual Relationship of Strategic Stances and Formulation Methods, and Their Impacts on Performance in Public Local Transit Agencies. Administration and Society. [Google Scholar] [CrossRef]
- Petter, Stacie, and Ephraim R. McLean. 2009. A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information and Management. [Google Scholar] [CrossRef]
- Petter, Stacie, William DeLone, and Ephraim McLean. 2008. Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems. [Google Scholar] [CrossRef]
- Pina, Vicente, Lourdes Torres, and Sonia Royo. 2010. Is e-government leading to more accountable and transparent local governments? An overall view. Financial Accountability & Management. [Google Scholar] [CrossRef]
- Poister, Theodore H., David W. Pitts, and Lauren Hamilton Edwards. 2010. Strategic management research in the public sector: A review, synthesis, and future directions. American Review of Public Administration. [Google Scholar] [CrossRef]
- Pollitt, Christopher, and Geert Bouckaert. 2004. The nature of public management reform. In Public Management Reform: A Comparative Analysis. New York: Oxford University Press. [Google Scholar]
- Prybutok, Victor R., Xiaoni Zhang, and Sherry D. Ryan. 2008. Evaluating leadership, IT quality, and net benefits in an e-government environment. Information and Management. [Google Scholar] [CrossRef]
- Rao, V. 2011. Collaborative Government to Employee (G2E): Issues and Challenges to E-Government. Journal of E-Governance. [Google Scholar] [CrossRef]
- Rokita-Poskart, Diana, and Łukasz Mach. 2019. Selected meso-economic consequences of the changing number of students in academic towns and cities (a case study of Poland). Sustainability 10: 1901. [Google Scholar] [CrossRef][Green Version]
- Sagarik, Danuvas, Pananda Chansukree, Wonhyuk Cho, and Evan Berman. 2018. E-government 4.0 in Thailand: The role of central agencies. Information Polity. [Google Scholar] [CrossRef][Green Version]
- Salvati, Eugenio. 2017. E-government and e-democracy in the supranational arena: The enforcing of transparency and democratic legitimacy in the European union. In Digital Media Integration for Participatory Democracy. Hershey: IGI Global. [Google Scholar] [CrossRef]
- Scholl, H. J., R. Fidel, S. Liua, M. Paulsmeyer, and K. Unsworth. 2007. E-Government Field Force Automation: Promises, Challenges, and Stakeholders. In Electronic Government. EGOV 2007. Edited by M. A. Wimmer, J. Scholl and Å Grönlund. Lecture Notes in Computer Science. Berlin and Heidelberg: Springer, vol. 4656. [Google Scholar]
- Sebaa, Ali Ahmed, James Wallace, and Nelarine Cornelius. 2009. Managerial characteristics, strategy and performance in local government. Measuring Business Excellence. [Google Scholar] [CrossRef]
- Segars, Albert H., and Varun Grover. 1993. Re-examining perceived ease of use and usefulness: A confirmatory factor analysis. MIS Quarterly: Management Information Systems 17: 517–25. [Google Scholar] [CrossRef]
- Staples, Warren, and John Dalrymple. 2016. Construction Procurement and State Government Strategy: Aligned or Disconnected? Australian Journal of Public Administration. [Google Scholar] [CrossRef]
- Tan, Chee-Wee, Shan L. Pan, and Eric T. K. Lim. 2007. Managing Stakeholder Interests in E-Government Implementation: Lessons Learned from a Singapore E-Government Project. International Journal of Electronic Government Research (IJEGR). [Google Scholar] [CrossRef]
- Teo, Thompson S. H., Shirish C. Srivastava, and Li Jiang. 2009. Trust and electronic government success: An empirical study. Journal of Management Information Systems. [Google Scholar] [CrossRef]
- Vakalopoulou, Melpomeni A., George Tsiotras, and Katerina Gotzamani. 2013. Implementing CAF in public administration. Benchmarking: An International Journal. [Google Scholar] [CrossRef]
- Verma, Neeta, and Alka Mishra. 2009. india.gov.in—India’s approach in constructing one-stop-solution towards e-Government. ACM International Conference Proceeding Series. [Google Scholar] [CrossRef]
- Walker, Richard M. 2013. Strategic management and performance in public organizations: Findings from the miles and snow framework. Public Administration Review. [Google Scholar] [CrossRef]
- Walker, Richard M., Rhys Andrews, George A. Boyne, Kenneth J. Meier, and Laurence J. O’Toole Jr. 2010. Wakeup call: Strategic management, network alarms, and performance. Public Administration Review. [Google Scholar] [CrossRef]
- Walker, Richard M., George A. Boyne, and Gene A. Brewer. 2013. Public management and performance: Research directions, Public Management and Performance: Research Directions. Cambridge: Cambridge University Press. [Google Scholar] [CrossRef]
- Wang, Yi-Shun, and Yi-Wen Liao. 2008. Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly. [Google Scholar] [CrossRef]
- Wolniak, Radoslaw, Bożena Skotnicka-Zasadzień, and Michał Zasadzień. 2019. Problems of the Functioning of E-Administration in the Silesian Region of Poland from the Perspective of a Person with Disabilities. Transylvanian Review of Administrative Sciences. [Google Scholar] [CrossRef]
- Wronka-Pośpiech, Martyna, and Aldona Frączkiewicz-Wronka. 2016. Strategic Orientation and Organisational Culture in Polish Public Organisations: Insights from the Miles and Snow Typology. Management. [Google Scholar] [CrossRef][Green Version]
- Yildiz, Mete. 2007. E-government research: Reviewing the literature, limitations, and ways forward. Government Information Quarterly. [Google Scholar] [CrossRef]
- Zheng, Yueping. 2017. Explaining Citizens’ E-Participation Usage. Administration & Society. [Google Scholar] [CrossRef]

**Table 1.**Model 1: Ordinary Least Squares (OLS), using observations 1–228. Dependent variable: Citizen 1.

Coefficient | Std. Error | t-Ratio | p-Value | ||
---|---|---|---|---|---|

Constant | 0.307856 | 0.313845 | 0.9809 | 0.3277 | |

Prospector | 0.556150 | 0.0883406 | 6.296 | <0.0001 | *** |

Defender | 0.351803 | 0.0992614 | 3.544 | 0.0005 | *** |

Mean dependent variable | 5.105263 | S.D. dependent variable | 1.261901 | ||

Sum squared residual | 161.4147 | S.E. of regression | 0.846994 | ||

R-squared | 0.553454 | Adjusted R-squared | 0.549484 | ||

F(2, 225) | 139.4336 | p-value (F) | 4.07 × 10^{−40} | ||

Log-likelihood | −284.1459 | Akaike criterion | 574.2919 | ||

Schwarz criterion | 584.5799 | Hannan–Quinn | 578.4428 |

Coefficient | Std. Error | t-Ratio | p-Value | ||||
---|---|---|---|---|---|---|---|

Constant | 1.23792 | 0.266207 | 4.650 | <0.0001 | *** | ||

Defender | 0.785115 | 0.0463647 | 16.93 | <0.0001 | *** | ||

Reactor | 0.143048 | 0.0665081 | 2.151 | 0.0326 | ** | ||

Analyzer | −0.152602 | 0.0590068 | −2.586 | 0.0103 | ** | ||

Mean dependent variable | 5.596491 | S.D. dependent variable | 1.051278 | ||||

Sum squared residual | 94.41589 | S.E. of regression | 0.649230 | ||||

R-squared | 0.623657 | Adjusted R-squared | 0.618617 | ||||

F(3, 224) | 123.7339 | p-value (F) | 2.77 × 10^{−47} | ||||

Log-likelihood | −223.0115 | Akaike criterion | 454.0229 | ||||

Schwarz criterion | 467.7403 | Hannan–Quinn | 459.5575 |

Coefficient | Std. Error | t-Ratio | p-Value | ||
---|---|---|---|---|---|

Constant | 1.10777 | 0.225377 | 4.915 | <0.0001 | *** |

Defender | 0.658995 | 0.0682294 | 9.659 | <0.0001 | *** |

Reactor | 0.163939 | 0.0568785 | 2.882 | 0.0043 | *** |

Analyzer | −0.179726 | 0.0505038 | −3.559 | 0.0005 | *** |

Prospector | 0.148437 | 0.0579851 | 2.560 | 0.0111 | ** |

Mean dependent variable | 5.521930 | S.D. dependent variable | 1.011803 | ||

Sum squared residual | 67.36426 | S.E. of regression | 0.549620 | ||

R-squared | 0.710125 | Adjusted R-squared | 0.704925 | ||

F(4, 223) | 136.5740 | p-value (F) | 8.72 × 10^{−59} | ||

Log-likelihood | −184.5257 | Akaike criterion | 379.0513 | ||

Schwarz criterion | 396.1980 | Hannan–Quinn | 385.9695 |

Coefficient | Std. Error | t-Ratio | p-Value | ||
---|---|---|---|---|---|

Constant | 1.10733 | 0.194827 | 5.684 | <0.0001 | *** |

Defender | 0.598966 | 0.0616190 | 9.720 | <0.0001 | *** |

Prospector | 0.177482 | 0.0548396 | 3.236 | 0.0014 | *** |

Mean dependent variable | 5.317982 | S.D. dependent variable | 0.934110 | ||

Sum squared residual | 62.20304 | S.E. of regression | 0.525793 | ||

R-squared | 0.685956 | Adjusted R-squared | 0.683165 | ||

F(2, 225) | 245.7304 | p-value (F) | 2.58 × 10^{−57} | ||

Log-likelihood | −175.4386 | Akaike criterion | 356.8772 | ||

Schwarz criterion | 367.1653 | Hannan–Quinn | 361.0281 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | 0.124221 | 0.356409 | 0.3485 | 0.7278 | ||||

Defender | 0.885564 | 0.0636904 | 13.90 | <0.0001 | *** | |||

Mean dependent variable | 5.000000 | S.D. dependent variable | 1.307383 | |||||

Sum squared residual | 209.1161 | S.E. of regression | 0.961921 | |||||

R-squared | 0.461041 | Adjusted R-squared | 0.458656 | |||||

F(1, 226) | 193.3268 | p-value (F) | 3.60× 10^{−32} | |||||

Log-likelihood | −313.6620 | Akaike criterion | 631.3240 | |||||

Schwarz criterion | 638.1827 | Hannan–Quinn | 634.0913 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | −0.0695592 | 0.412185 | −0.1688 | 0.8661 | ||||

Defender | 0.842053 | 0.0665854 | 12.65 | <0.0001 | *** | |||

Analyzer | 0.0848740 | 0.0482671 | 1.758 | 0.0800 | * | |||

Mean dependent variable | 4.894737 | S.D. dependent variable | 1.316573 | |||||

Sum squared residual | 227.3766 | S.E. of regression | 1.005267 | |||||

R-squared | 0.422130 | Adjusted R-squared | 0.416994 | |||||

F(2, 225) | 82.18053 | p-value (F) | 1.61 × 10^{−27} | |||||

Log-likelihood | −323.2058 | Akaike criterion | 652.4117 | |||||

Schwarz criterion | 662.6997 | Hannan–Quinn | 656.5626 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | 0.144551 | 0.361619 | 0.3997 | 0.6897 | ||||

Defender | 0.803616 | 0.0615148 | 13.06 | <0.0001 | *** | |||

Reactor | 0.110531 | 0.0489315 | 2.259 | 0.0248 | ** | |||

Mean dependent variable | 5.052632 | S.D. dependent variable | 1.237036 | |||||

Sum squared residual | 183.9401 | S.E. of regression | 0.904163 | |||||

R-squared | 0.470476 | Adjusted R-squared | 0.465769 | |||||

F(2, 225) | 99.95477 | p-value (F) | 8.65 × 10^{−32} | |||||

Log-likelihood | −299.0381 | Akaike criterion | 604.0763 | |||||

Schwarz criterion | 614.3643 | Hannan–Quinn | 608.2272 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | 0.612347 | 0.383093 | 1.598 | 0.1114 | ||||

Defender | 0.776268 | 0.0618859 | 12.54 | <0.0001 | *** | |||

Analyzer | 0.0543611 | 0.0448605 | 1.212 | 0.2269 | ||||

Mean dependent variable | 5.096491 | S.D. dependent variable | 1.216403 | |||||

Sum squared residual | 196.4135 | S.E. of regression | 0.934317 | |||||

R-squared | 0.415222 | Adjusted R-squared | 0.410024 | |||||

F(2, 225) | 79.88083 | p-value (F) | 6.12 × 10^{−27} | |||||

Log-likelihood | −306.5179 | Akaike criterion | 619.0358 | |||||

Schwarz criterion | 629.3238 | Hannan–Quinn | 623.1867 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | 0.664728 | 0.239624 | 2.774 | 0.0060 | *** | |||

Defender | 0.575955 | 0.0725423 | 7.940 | <0.0001 | *** | |||

Prospector | 0.182334 | 0.0616505 | 2.958 | 0.0034 | *** | |||

Reactor | 0.348458 | 0.0604739 | 5.762 | <0.0001 | *** | |||

Analyzer | −0.240453 | 0.0536963 | −4.478 | <0.0001 | *** | |||

Mean dependent variable | 5.368421 | S.D. dependent variable | 1.047448 | |||||

Sum squared residual | 76.14996 | S.E. of regression | 0.584363 | |||||

R-squared | 0.694242 | Adjusted R-squared | 0.688757 | |||||

F(4, 223) | 126.5834 | p-value (F) | 3.27 × 10^{−56} | |||||

Log-likelihood | −198.5009 | Akaike criterion | 407.0018 | |||||

Schwarz criterion | 424.1485 | Hannan–Quinn | 413.9200 |

Coefficient | Std. Error | t-Ratio | p-Value | |||||
---|---|---|---|---|---|---|---|---|

Constant | 0.722037 | 0.248889 | 2.901 | 0.0041 | *** | |||

Defender | 0.594410 | 0.0753473 | 7.889 | <0.0001 | *** | |||

Prospector | 0.177097 | 0.0640344 | 2.766 | 0.0062 | *** | |||

Reactor | 0.240274 | 0.0628122 | 3.825 | 0.0002 | *** | |||

Analyzer | −0.156714 | 0.0557726 | −2.810 | 0.0054 | *** | |||

Mean dependent variable | 5.350877 | S.D. dependent variable | 1.036620 | |||||

Sum squared residual | 82.15277 | S.E. of regression | 0.606958 | |||||

R-squared | 0.663211 | Adjusted R-squared | 0.657170 | |||||

F(4, 223) | 109.7841 | p-value (F) | 1.50 × 10^{−51} | |||||

Log-likelihood | −207.1508 | Akaike criterion | 424.3015 | |||||

Schwarz criterion | 441.4483 | Hannan–Quinn | 431.2197 |

Coefficient | Std. Error | t-Ratio | p-Value | |||
---|---|---|---|---|---|---|

Constant | 0.824202 | 0.250868 | 3.285 | 0.0012 | *** | |

Defender | 0.618028 | 0.0759463 | 8.138 | <0.0001 | *** | |

Prospector | 0.157283 | 0.0645434 | 2.437 | 0.0156 | ** | |

Reactor | 0.308120 | 0.0633116 | 4.867 | <0.0001 | *** | |

Analyzer | −0.246773 | 0.0562160 | −4.390 | <0.0001 | *** | |

Mean dependent variable | 5.429825 | S.D. dependent variable | 1.061703 | |||

Sum squared residual | 83.46419 | S.E. of regression | 0.611783 | |||

R-squared | 0.673812 | Adjusted R-squared | 0.667961 | |||

F(4, 223) | 115.1635 | p-value (F) | 4.30 × 10^{−53} | |||

Log-likelihood | −208.9562 | Akaike criterion | 427.9124 | |||

Schwarz criterion | 445.0591 | Hannan–Quinn | 434.8306 |

Coefficient | Std. Error | t-Ratio | p-Value | |||
---|---|---|---|---|---|---|

Constant | 1.18248 | 0.249905 | 4.732 | <0.0001 | *** | |

Defender | 0.785628 | 0.0425112 | 18.48 | <0.0001 | *** | |

Reactor | 0.0202239 | 0.0338152 | 0.5981 | 0.5504 | ||

Mean dependent variable | 5.596491 | S.D. dependent variable | 1.008504 | |||

Sum squared residual | 87.84626 | S.E. of regression | 0.624842 | |||

R-squared | 0.619511 | Adjusted R-squared | 0.616129 | |||

F(2, 225) | 183.1720 | p-value (F) | 6.14 × 10^{−48} | |||

Log-likelihood | −214.7896 | Akaike criterion | 435.5793 | |||

Schwarz criterion | 445.8673 | Hannan–Quinn | 439.7302 |

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Hawrysz, L.
Strategic Orientation and Effects of E-Administration: Findings from the Miles and Snow Framework. *Adm. Sci.* **2020**, *10*, 35.
https://doi.org/10.3390/admsci10020035

**AMA Style**

Hawrysz L.
Strategic Orientation and Effects of E-Administration: Findings from the Miles and Snow Framework. *Administrative Sciences*. 2020; 10(2):35.
https://doi.org/10.3390/admsci10020035

**Chicago/Turabian Style**

Hawrysz, Liliana.
2020. "Strategic Orientation and Effects of E-Administration: Findings from the Miles and Snow Framework" *Administrative Sciences* 10, no. 2: 35.
https://doi.org/10.3390/admsci10020035