02075nas a2200253   4500008004100000022001400041245007700055210006900132260004200201300001000243490000600253520135000259653001301609653001501622653001201637653001701649653002001666653001301686653002301699100001901722700002101741700002101762856003801783       2019                        eng d  a1927-032100aDigital Payments: Impact Factors and Mass Adoption in Sub-Saharan Africa0 aDigital Payments Impact Factors and Mass Adoption in SubSaharan   aOttawabTalent First Networkc07/2019  a41-550 v93 aThis study explores impact factors that affect the adoption of digital payment systems in sub-Saharan Africa. In this article, we investigate the impact factors that subject-matter experts consider most important to the success of FinTech payment models. The data and their responses are evaluated through the lens of Christensen’s market-creation theory, which contends that the adoption of market-creating innovations by a mass swathe of heretofore non-consumers “pulls” framework conditions into place, including missing infrastructure and enabling regulation. Then, we compare the findings with the literature and three case studies of mobile money adoption in Kenya, South Africa, and Nigeria. This study addresses a gap in the literature regarding the payment and money transfer segment of FinTech innovations in Africa using a multiple case study methodology. We drew together information from multiple sources, including semi-structured interviews, archival data in the form of industry and regulatory reports, and observational field notes. Our findings suggest that enabling environments (Kenya) do jumpstart adoption and difficult frameworks (Nigeria) do evolve. This study will help FinTech innovators, academics, and policymakers to understand how technology and framework conditions impact payment business models in Africa. 10aadoption10ablockchain10aFinTech10amobile money10anon-consumption10apayments10asub-Saharan Africa1 aSoutter, Leigh1 aFerguson, Kenzie1 aNeubert, Michael  uhttps://timreview.ca/article/125400757nas a2200289   4500008004100000022001400041245003600055210003300091260004200124300000800166490000600174653001700180653001300197653001100210653001700221653002400238653002000262653001100282653002100293653002100314653001500335653002600350653001000376653002500386100001800411856003800429       2019                        eng d  a1927-032100aEditorial: Insights (July 2019)0 aEditorial Insights July 2019  aOttawabTalent First Networkc07/2019  a3-40 v910aaccelerators10aadoption10aAfrica10aarchitecture10abusiness ecosystems10abusiness models10adesign10adigital payments10aentrepreneurship10aincubators10aInnovation management10aISPIM10aknowledge management1 aMcPhee, Chris  uhttps://timreview.ca/article/125002332nas a2200277   4500008004100000022001400041245008600055210006900141260004200210300001000252490000600262520153500268653001301803653001601816653003101832653001501863653002801878653001401906653001901920653001501939653001501954653001401969100001801983700001702001856003602018       2014                        eng d  a1927-032100aCybersecurity Capability Maturity Models for Providers of Critical Infrastructure0 aCybersecurity Capability Maturity Models for Providers of Critic  aOttawabTalent First Networkc10/2014  a33-390 v43 aCritical infrastructure such as power generation and distribution systems, telecommunications networks, pipelines and pipeline control networks, transportation control networks, financial networks, and government information and communications technology (ICT) have increasingly become the target of cyber-attacks. The impact and cost of these threats, as well as regulatory pressure to mitigate them, have created an impetus to secure these critical infrastructures. Managers have many controls and models at their disposal to help them secure infrastructure technology, including cybersecurity capability maturity models to enable measurement and communication of cybersecurity readiness to top management teams, regulators, and customers, thereby facilitating regulatory compliance, corporate responsibility, and improved brand quality. However, information and awareness is lacking about which models are most appropriate for a given situation and how they should be deployed.

This article examines relevant cybersecurity capability maturity models to identify the standards and controls available to providers of critical infrastructure in an effort to improve their level of security preparedness. These capability models are described and categorized by their relevance to different infrastructure domains, and then recommendations are provided on employing capability maturity models to measure and communicate readiness. This article will be relevant to regulators, critical infrastructure providers, and researchers. 10aadoption10abersecurity10acapability maturity models10acompliance10acritical infrastructure10aframework10amunicipalities10aprotection10aregulation10astandards1 aMiron, Walter1 aMuita, Kevin  uhttp://timreview.ca/article/83701620nas a2200217   4500008003900000022001400039245011400053210006900167260004200236300001000278490000600288520094300294653001301237653001301250653002701263653002001290653001801310100001601328700002201344856003601366       2012                          d  a1927-032100aA Business Application of the System Dynamics Approach: Word-of-Mouth and Its Effect in an Online Environment0 aBusiness Application of the System Dynamics Approach WordofMouth  aOttawabTalent First Networkc06/2012  a42-480 v23 aIn this article, we illustrate the use of system dynamics modeling approach to study a complex system: word-of-mouth. Word-of-mouth plays an important role in reducing risk and uncertainty in purchase and consumption. Most of the prior research on word-of-mouth focused on studying either the factors that trigger consumers’ participation (sending or receiving) in word-of-mouth activities or the impact word-of-mouth information has on consumers’ buying decisions. The relationship between the two decision processes, however, is recursive and dynamic. Most prior studies have not focused on a recursive relationship. Our objective is to present a system dynamics model for the study of the relationship between the buying decision and the decision to participate in word-of-mouth communication. We also discuss how system dynamics modeling can be used in other complex problems in business such as the creation of a global business.10aadoption10amodeling10arecursive relationship10asystem dynamics10aword-of-mouth1 aWong, Roman1 aSheng, Shirley Ye  uhttp://timreview.ca/article/568