E. Vince Carter
Digital business marketing strategy is a complex coordination of confluent macro, meso (mediating), and micro market factors. Yet, the strategic challenges of digital transformation are often misdiagnosed as symptoms of micro-market business models, or as signs of meso-market technology channels, when causes commonly originate in turbulent macro-market conditions. Thus, this paper contributes a heuristic digital market navigation map based on the holistic nature of digital market parameters, comprising macro, meso, and micro domains. After establishing the digital market’s conceptual foundations, a qualitative meta-theoretical analysis is conducted to examine the efficacy of current marketing systems and digital market frameworks. Best practices are derived from the meta-theoretical analysis and distilled into research propositions for designing the Dynamic Digital Market Sphere (DDMS) model. The DDMS model is advanced as an improved digital business strategy template for navigating the digital market’s transformative nature with greater mapping depiction, dynamism, directionality, dialectic, and discovery.
E. Vince Carter, Ph.D. Associate Professor of Marketing Dept. of Management & Marketing
California State University, Bakersfield 9001 Stockdale Highway; 20 BDC
Bakersfield, CA 93311-1022
The digital economy is marked by a wider web of connections with higher turbulence and complexity causing waves of change to ripple through the global market system (UNCTAD 2019; OECD 2019, 2017, Tapscott 1994). According to Mason and Staude (2009, p. 174-174), “Change occurs in two major dimensions: complexity and turbulence.
As complexity increases, the ability to understand, plan and predict becomes more difficult.” These turbulent environmental dynamics are characterized as chaotic and
conceptualized using “chaos theory” (Samli 2006; Doherty and Delener 2001; Conner 1998;
Samli 1993), and the complexity spawned by rising turbulence is modeled as “complex adaptive systems” (CASs) comprising holistic environmental forces (Wollin and Perry 2004, Kelly and Allison 1999). These turbulent conditions are characterized as a “digital vortex” (Bradley et al. 2015) accelerating the urgency of “digital transformation” (VanVeldhoven 2021). So, digital business strategy must be adept, adaptive, agile
capabilities (Nadeem et al. 2018; Bharadwaj et al. 2013; Davis, Eisenhardt, Bingham 2009).
Some view digital market transformation as a shift towards an open and connected network paradigm and complex adaptive market system, versus the traditional disconnected system of socio-economic exchanges (Achrol and Kotler 2012, 1999; Achrol 1996, 1991; Castells 1996; Miles and Snow 1995). Others see the digital economy laying a network infrastructure for more inclusive circular connections across societal sectors, with collaborative strategic/sustainability planning and feedback loops throughout the marketing system (Murray, Skene, and Haynes 2017; MacArthur 2013). So, ‘digital market’ conveys a ubiquitous, dynamic, and transformative digital economy sphere.
Despite general agreement on the macro-market environment origin of the turbulence in digital market dynamics, digital business strategies are often narrowly focused on micro- market supply and demand factors. New digital and social-media marketing mix programs are formulated with big data analytics algorithms then targeted towards real-time digital customer screens, agents, and apps. The e-commerce infrastructure, automated warehouses, satellite tracking logistical systems, and smart delivery services of market intermediary networks are regularly incorporated in digital business plans. Yet, pervasive macro-market sources of transformation are seldom prioritized and proactively mapped for strategic plans.
A foundation for balancing macro-market turbulence with micro-market strategy and structure is laid by Davis, Eisenhardt, and Bingham (2009) by identifying four key
“Environmental Dynamism Dimensions” – velocity, complexity, ambiguity, and unpredictability (pp. 415, 420). More recently, Bharadwaj et al. (2013) formulated a model of macro environment and micro enterprise forces specifically for digital business strategy. They posit “key external digital trends” as the proactive source of “key organizational shifts,” and “drivers of the four key themes of digital business strategy” – scope, scale,
speed of decisions, and sources of value (p. 473). Samli (2006) describes the macro-market environment as chaotic, complex, and in perpetual disequilibrium. In response, a “Counterchaos Strategy” is advanced consisting of five sequential elements – detection, conversion, evaluation, facilitation, and implementation (Samli 2006, p.321). In particular, the first three elements impart a strategic macro-market scope for detecting dynamic trends, converting them into micro-market opportunities, and evaluating value creation priorities.
Consequently, given the extant literature’s inadequate digital reality scope this study advances a more holistic conceptualization of the digital market’s nature and navigation. The paper proceeds by first establishing digital market design ground rules by tracing conceptual foundations. Then, a sample of digital/market frameworks is compiled from a topic keyword literature search and evaluated using qualitative meta-theoretical analysis. Next, meta-analysis findings are distilled into research propositions for five strategic design parameters (depiction, dynamism, directionality, dialectic, and discovery) to advance an improved Dynamic Digital Market Sphere (DDMS) model. A closing discussion applies the DDMS model as a template for aligning structural nature with strategic navigation.
The macro environment forces driving digital market dynamism require a holistic and comprehensive mapping of digital market domains and dimensions to direct digital business strategy. These dynamic and pervasive forces are the focus of recent research addressing “digital transformation” in business models and strategies (VanVeldhoven 2021; OECD 2019; Schallmo, Williams, and Boardman 2017; Nadeem et al. 2018; Berger 2015). Transformative business models are described as “six keys to success,” including a “collaborative ecosystem” for facilitating an “agile and adaptive organization” by Kavadias, Ladas, and Loch (2016, p.4). Ironically, none of these transformative digital business models fully captures the external macro environment sources of turbulence and dynamism, and therefore have limited ubiquity. Accordingly, this exploratory study in theory construction examines the descriptive and dynamic origins of marketing theory for framing the digital market. A cross-disciplinary meta-analysis of frameworks is then applied to yield a more viable model of the digital market’s structural nature for strategic navigation.
Descriptive Foundations
Marketing scholars frame a holistic and strategic view of the marketing system’s macro environment, micro engagement, and interconnected participants (Brownlie 1991; Glaser 1985; Hunt and Burnett 1982; Hunt 1976; Bartels 1968; Mackenzie and Nicosia 1968; Breyer 1934). The digital market’s cyclical current of electronic commerce is prefigured by Breyer’s (1934) marketing system model as analogous to an electrical circuit. Later,
Alderson’s (1965) description of a “functionalist theory of marketing” harnesses dynamic marketing system forces. Eventually, Hunt’s (1978) logical deduction of the “micro/macro
dichotomy” is cast as central to the “nature and scope of marketing” – paving the way for a micromarketing/micromarketing taxonomy (Hunt and Burnett 1982).
Soon thereafter, Glaser (1985) draws on cybernetics theory to delineate a symbiotic signaling mechanism between the marketing system’s macro causes and micro
consequences. Applying the Emery and Trist’s (1965) “turbulent environment”
determinants, Glaser distinguishes between “variety increasing” transaction signals that emerge from macro marketing system vastness, and “variety decreasing” interactive exchange signals that enable micro marketing system value.
The common thread of environmental determinism in marketing system dynamics accounts for Brownlie’s (1991) strategic rubric for scanning and analyzing macro-market factor trends to yield reliable micro-market forecasting techniques. These descriptive contributions of marketing scholars are distilled into the “modern marketing system” (Perreault, Cannon, and McCarthy 2019; Kotler and Armstrong 2018), and provides a pliable digital market diagram. This descriptive marketing system duality is congruent with the dynamic formation of marketing system flows and reinforces the prevalence of macro environment forces driving digital market strategy.
Dynamic Formation
Although a descriptive picture is presented by foundational frameworks, they do not adequately portray the digital market’s dynamic processes and value creation purposes. Recognizing the temporal, transactional, transcending, and transformational marketing system propensities, early marketing visionaries configured a holistic, interconnected, and continuously flowing/fusing model of marketing system forces (Layton 2007; Dowling 1983; Dixon and Wilkerson 1982; Bagozzi 1975; Fisk 1967; McInnes 1964). These marketing system dynamics, initially defined as “transactions and transvections,” (Alderson 1965; Alderson and Martin 1965), have adapted to the digital market as “hypermedia computer-mediated environments” (Hoffman and Novak 1997, 1996), the “network economy/firm/paradigm,” (Achrol and Kotler 1999; Achrol 1996; Castells 1996; Miles and Snow 1995), and “symbolic interactionism” for exchanging “competency codes.” (Kadirov and Varey 2011; Carter 2009; Varey 2008; Venkatesh, Penaloza, and Firat 2006).
Game Boards – Meta-Analysis of Digital Market Frameworks
In order to determine whether existing marketing system and digital market frameworks meet the necessary and sufficient criteria for strategic application, a qualitative meta- theoretical analysis is conducted. The criteria are strategic visual representation of digital market depiction, dynamism, directionality, dialectic, and discovery. Meta-theoretical analysis is a valid assessment procedure (Lucarelli and Brorström 2013; Ritzer 2001, 1991;
Zhao 1991), and qualitative analysis is appropriate for conceptual, holistic, and exploratory subject matter (Berg 2009; Belk 2007).
The primary research aims are to survey, score, and synthesize the existing marketing system and digital market frameworks, as well as to substantiate propositions for an improved Dynamic Digital Market Sphere (DDMS) model. As a result, two main research objectives are specified for exploratory inquiry, with propositions defined for each research objective similar to hypotheses for conclusive quantitative research.
Examine existing “Marketing System” and “Digital Market” frameworks.
Proposition 1 – Digital/Marketing System frameworks differ in their visual design of top-down holistic comprehensiveness based on ubiquity properties, as well as the depiction of macro, meso, micro domain factors – including strategic functions and customer profiles.
These traits are addressed by the depiction criterion.
Proposition 2 – Digital/Marketing System frameworks differ based on their ability to visually design fluidity as dynamic interaction, resource flows, domain orientation, as well as strategically guided patterns of networks/nodes and roles involved in flow interactions.
These traits are addressed by dynamism & directionality criteria.
Expound new “Digital Market” framework parameters.
Proposition 3 – Digital/Marketing System frameworks differ in their visual design of individual bottom-up dialectic interaction among domain factors and sub-factors, to indicate agency and adaptation properties that can be strategically aligned.
These traits are addressed by the dialectic criterion.
Proposition 4 – Digital/Marketing System frameworks differ by their level of visual variance in the design and detailing of domain factors and sub-factor items to optimize strategic scanning/sensing of those elements, as well as raise the potential for serendipitous and spontaneous discovery of strategic digital market opportunities.
These traits are addressed by the discovery criterion.
A final sample of 36 frameworks contains a representative range of holistic and partial digital/marketing system designs across multiple fields of study, addressing various macro and micro-orientations, with differing modeling purposes. The systematic sample selection plan intentionally includes frameworks focused on specific domains for collective,
company, or customer factors. Even if frameworks are rated low, each one contributes to an improved map of the digital market’s nature for business strategy navigation. Cumulative insights from the meta-analysis are incorporated into the proposed DDMS model. The criteria of depiction, dynamism, directionality, dialectic, and discovery are applied to evaluate each framework.
Depiction takes a top-down view to evaluates how frameworks represent:
aggregate and/or individual market entities,
as homogeneous units or with heterogeneous features,
in a holistic comprehensive or hewn compartmental manner, and
which of three (3) domain/proximity spheres are included, with or without factors specified:
macro: external -- demographic, economic, social-cultural, technology, ecology, political-legal
meso:
externally-oriented – macro mediators: market publics, intermediaries, stakeholders, etc.
internally-oriented – micro mediators ‘Ms’: organization portals, interfaces, modes, etc.
micro:
external -- customers and competitors
internal – company and strategy functions.
*Note: Framework elements are examined for meanings, not merely labels. Many frameworks omit the meso domain and label publics and intermediaries as micro. Also, competition macro or micro.
Dynamism evaluates the framework and its entities for their:
degree of fixity or fluidity,
interactions or networks linking entities and crossing domains.
facilitation of resource flows, adaptations, and temporality
Directionality evaluates the framework’s main orientation, strategic priorities, and influence patterns:
macro to micro (outside-in), micro to macro (inside-out), meso to micro/macro (middle out/in or in/out), as well as neutral
roles of domains and entities in regulating or changing flow direction.
*Note: Macro (outside-in) orientation is prioritized to address responsiveness to rising macro environment factor prominence as a source of micro and meso domain turbulence.
Dialectic takes a bottom-up view to evaluate how the frameworks design:
autonomy among market factors that enables a variety of interactions.
agency to form within factor combinations and/or between factors.
alignment across domains and factors for strategic/societal advantage
adaptation to power shifts, time cycles, and participation conditions
Discovery evaluates the frameworks overall innovativeness potential, to:
reveal opportunities with novel system combinations and calibrations.
reward risk-taking with spontaneous patterns of market scope/scale
recognize serendipitous possibilities with domain decision scenarios.
An iterative meta-analysis was performed by examining each theoretical framework according to the research objectives, propositions, sample screening, and measurement criteria stipulated above. The study’s analytical outcomes and criteria evaluations are presented as a graphical taxonomy in Figure 1. The condensed graphical images aid
interpretation and are not for detailed inspection. Letter grades are used in lieu of numerical ratings/rankings to stress the nominal measures for qualitative analysis. In addition, a
“visual vs. functional” notation pertains to evaluations that are based on framework elements that can be seen or visibly mapped, not on the functional application of the framework’s implied guidance which is indicated but not visual. Likewise, a “partial diagram” notation means that the complete framework includes additional visual diagram details that are not shown but included in the evaluation ratings.
Table 1 contains a taxonomy of meta-theoretical analysis findings in seven separate panels divided by academic field, macro/micro-orientation, and strategic angle. These meta- analysis sample entries are collectively described as ‘digital/market’ frameworks. The panels proceed from basic economic market theory and business/marketing system foundations described earlier, to more complex, comprehensive, and compartmentalized models for the digital market. As described above, the entries are shown in the taxonomy with five columns for evaluating digital market design parameters using the strategic criteria of depiction, dynamism, directionality, dialectic, and discovery.
Panel I contain the basic systems frameworks designed for descriptive academic instruction and policy making. They depict the economic “market system” circular flow model in the first row and alternative views of the business “modern marketing system” in the following three rows. The evaluations improve as the framework entries progress, with noticeably better detail and intricacy – especially for depicting factors in the three domains (e.g., macro, meso, and micro). The Marketing Information System charts intelligence and data flows, while the other two frameworks diagram the marketing system.
Panel II frameworks focus on the micro domain company strategy element with multiple versions of the triangle model – in lieu of traditional “4Ps” marketing mix elements.
Because of this narrow micro company focus, all three frameworks are low on each criterion. Yet, the efficacy and parsimony of the triangular representation of company strategy informs improved digital market modeling. Five similar triangular frameworks are noted in the bottom row with a single combined evaluation.
Panel III focuses on micro-oriented frameworks applied to digital business/marketing strategy. The panel proceeds from a relatively highly rated comprehensive model of macro, meso, and micro strategy domain factors, to average ratings for two models customized for micro digital business/marketing strategy processes, and a low rated les holistically representative heuristic matrix of digital strategy options on the bottom row. Thus, Panel III highlights strategic alignments between digital micro functions and macro/meso forces.
Panel IV extends the micro-orientation to frameworks mapping digital consumer cognition. The panel proceeds from the consumer’s digital hypermedia content “flow” engagement to fundamental digital user interface models for technology acceptance (TAM UTAUT/2). Then, e-commerce/web market interaction elements are configured (E-TAM, SE-TAM). Finally, the bottom row adds a model of “tech-based self-service” digital market conduciveness. Each of the models address the vital coupling of cognition and computing
for digital market consumption. Yet the overly tailored cognitive view results in low scores for a grossly incomplete representation of the digital market. Taken together, Panel IV addresses the range of consumer cognitive risks/reward variables in digital market strategy.
Panel V completes the micro-oriented frameworks with four models that take a fully holistic angle towards configuring digital marketing strategy. Consequently, this panel culminates the micro strategy orientation with “network,” “constellation,” and
“Marketology” frameworks incorporating all three domains (e.g., macro, meso, micro), including detailed factors addressing environmental conditions, intermediary contingencies, and the strategic coupling of company/customer aims. Accordingly, each framework earns top ratings. Thus, Panel V contributes viable micro-oriented digital market designs.
Panel VI transitions to macro-oriented frameworks that chart the total business
“ecosystem” and societal “ecology,” rather than to plan micro digital business/marketing strategy. The “business ecosystems” frameworks are rated relatively high for reinforcing the business “ecology” as a definitive pattern for the turbulent macro environment and for inserting the role of meso “capitals” as mediators of digital market transformation. The
remaining two “ecosystem” frameworks only address external factors for ecological environmental management purposes. However, they improve digital market modeling of the macro domain as well as highlight the imperative of eco-sustainability strategies for digital markets. In sum, Panel VI charts the macro-orientation of digital markets with partially holistic and dynamic patterns.
Panel VII consummates the macro-oriented frameworks with fully holistic representations of the digital market domains (e.g., macro, meso, micro), including micro business strategy angles. Although the frameworks do not specifically address meso mediating influences and company/customer interaction, those strategic digital market
iterations are implied in each model’s dimensions. While the first two frameworks are comprehensively descriptive, the last two rows portray distinctively dynamic holistic models for both social innovation and digital transformation. Clearly, the comprehensive depiction of macro, meso, micro domains render the “ecology” models as a benchmark for
digital market designs. Likewise, the “Quadruple Helix Open Innovation Model” (Yun and Liu 2019) includes a “quadruple helix” for modeling dynamic interaction and “open
innovation” outcomes which captures digital market complexity. In addition, the “Digital Transformation Framework” (Van Veldhoven and Vanthienen 2021) on the bottom row is a holistic digital market/society compass that provides precise three-dimensional indicators for intricate business, society, technology strategy. This comprehensive, complex, and customizable model earns top ratings. The other Panel VII frameworks in preceding rows in relatively high ratings for macro-oriented holistic depiction (ecology models) and “open innovation” agency (Quadruple Helix Model), but the absence of precise elements for micro-strategy direction prevents top ratings. Thus, Panel VII frameworks have the combined set of digital market design parameters to serve as macro-oriented benchmarks.
Distilling Meta-Analysis Findings into an Improved Digital Market Model
All four of the exploratory research propositions were affirmed by the meta-theoretical analysis findings. Specifically, the sample frameworks differed significantly in their capacity to: (a) visually depict holistic digital market parameters with macro, meso, and micro domains – including micro company and customer factors, (b) visually design dynamic interactivity, resource flows, domain orientation, as well as the strategically guided patterns and roles involved in flow interactions, (c) visually design domain factor and sub- factor item dialectic interaction with agency and adaptation properties that can be strategically aligned, and (d) the level of visual variance in the design and detailing of domain factor items to optimize strategic scanning/sensing, as well as raise the potential for serendipitous and spontaneous discovery of strategic digital market opportunities.
Theory construction rationale combines those qualitative analysis findings to design an improved digital market design, with Wacker’s (2008, 2004, 1998) four basic principles:
Definitions of terms or variables for a concept
Domain limitations to identify where the theory is applied
A set of relationships among variables
Measurement predictions and method for proving factual claims.
Table 2 presents the theory construction validation for the proposed DDMS model. The DDMS model’s connotative structural properties are defined as digital market domains (macro, meso, and micro) as well as the digital market dimensions (ubiquity and fluidity). The denoted DDMS model parameters are operationalized to direct holistic macro-market orientation, teleological three-domain alignment with relational factor agency, and ontological business/marketing strategy vectors. This combined DDMS design achieves planning congruity between the realistic nature and rational navigation of digital market dynamism. Finally, DDMS model planning scenarios identify normative outcomes.
Following theory construction procedures and incorporating findings from the meta- theoretical analysis, the proposed DDMS model is designed to improve the semantic nature and strategic navigation of digital market frameworks. The digital market’s semantic nature identifies domains, forces, dimensions, factors, and relationships. Likewise, digital market strategic navigation aligns those digital market model parameters with strategic digital business aims, agency, and adaptations.
Two primary parameters determine how the digital market ecology organizes and operates – domains and dimensions. First, domains organize digital market forces/factors
and dimensions direct their operation. Guided by the societal ecology configuration incorporated by several existing models (Wang 2021, 2018; Yun and Liu 2019; Perreault, et al. 2019; Wang, et al. 2015; Lee and Kotler 2015; Chaffey and Ellis-Chadwick 2012; Moore 2016, 2006, 1998, 1996, 1993; Brownlie 1991; Kotler, et al. 1991; Bronfenbrenner 1979) the digital market is modeled with an ecological pattern of three overlapping spheres – macro, meso, and micro.
Secondly, dimensions can be distilled into two patterns representing the vastness of digital market scope and valence of digital market scale. These dimensions align and adapt the direction of digital market strategy. The seminal marketing theory of “transactions and transvections” (Alderson 1965; Alderson and Martin 1965) is ideal for synthesizing the mapping and measurement of digital market interaction breadth and depth. Transactions constitute the conduit channels and media that connect market exchanges. Transvections
comprise the content value transformation that occurs in relation to and as a result of market exchanges. So, transactions map the vast scope or breath of digital market network interactions. Whereas transvections measure the valence scale or depth of digital market knowledge innovation. For the DDMS model “ubiquity” is specified as the transaction
property of breadth and vastness scope. Likewise, “fluidity” is specified as the transvection property of depth and valence scale. In addition, Wilkinson and Young (2005) contribute normative marketing system notions of dynamism, interconnection, and adaptive complexity to augment understanding of these two definitive digital market dimensions.
These added considerations address how digital market velocity is accelerating dynamic turbulence, boundary spanning connectivity, and disruptive complexity. (See Figure 2)
Macro-Market Environment
The macro-market environment is the starting point for digital market strategy because uncontrollable forces can pose long term and wide-spread opportunities or threats. The logic of strategic time/breadth horizons divides the macro-market environment into two external domains for “societal/contextual” and “task/transactional” forces (Vasconcelos and Ramirez 2011; Polonsky 1999; Zeithaml and Zeithaml 1984). Macro societal/contextual forces have the longest time frame and widest scope. The “DESTEP” acronym specifies six forces – demographic, economic, social-cultural, technological, ecological, and political-legal (Marketing Insider 2018). Institutional theory affirms this symbiosis of firms and the external environment (Scott 2004; Handelman and Arnold 1999; Pandya and Dholakia 1992), while “megamarketing” asserts proactive strategies for actualizing macro-market opportunities (Chaney, Slimane, and Humphreys 2016; Kotler 2011; Humphreys 2010; Kotler 1986). Although strategies are typically aimed at micro company objectives and myopic customer orientation, the digital market’s vastness, valence, and velocity requires proactive strategies that leverage macro-market trends with meso-market mediators.
Meso-Market Enablers
The other ‘external’ domain is described as a ‘task,’ ‘transactional,’ or ‘mediating’ environment, because it contains processes directly related to ‘internal’ marketing strategy and facilitates the material, social, and informational processing of ‘macro’ trend effects
into ‘micro’ value engagement. Perhaps the most common business/marketing strategy
phrase is “task environment” (Kotler and Keller 2016). Yet, the more descriptive and cross- disciplinary term ‘meso-market enablers’ is used for this conceptual charting, to draw upon the usage in sociology, ecology, anthropology, and global socioeconomics as a mediating domain (Rourke 2001; Blalock 1979). In systems design nomenclature ‘meso’ is a balancing and buffering band (Liljenstrom and Svedin 2005). Ultimately, meso-market
enablers create “shared value” (Porter and Kramer 2011) between digital business enterprises, internal resources and external intermediaries.
Meso Enablers as Macro Condition Mediators
A wheel of meso-market mediators is aligned with the inner macro domain boundary to filter and leverage external market environment conditions. This role of macro domain mediation enables strategic opportunities and business capabilities to be harnessed from the external environment’s dynamism and disruption. As such, these externally oriented meso- market enablers facilitate strategic growth by fostering an adaptive digital market equilibrium. Consequently, the mediating function of meso-market enablers is designed using the socio-economic concept of “capital” creation, cultivation, and currency. Russ and
Jones (2008) designate “knowledge capitals” as mediating filters for business ecosystems, while Moore (2006) assigns meso intermediaries to an “extended enterprise.”
Guided by frameworks for “capital building” (Castillo 2016) and “community capitals” (Emery and Flora 2006), a portfolio of meso enabling capitals is devised for transforming macro-environment resources into micro-environment results. Just as financial or economic capital flows to digital businesses with greater financial capability, other non-financial sources of market power can also be regarded as forms of ‘capital.’ Bourdieu’s (1986, 1984) seminal thesis on “the forms of capital” defines three other sources as “social, cultural, and symbolic capital.” Yet, human social relations, cultural habitus, symbolic meanings, and other conducive capabilities are also contained digital meso-market intermediary networks and processes. Drawing on extant studies of temporal, human, built, and natural capital (Hollenbeck and Jamieson 2015; Hunt 2014; Wang 2013; Tallis 2011; Bryan, Grandgirard,
and Ward 2010; Becker 2009; Hoffman 2009; Hassan 2007; Usunier and Valette-Florence 2007; Adam 2004; Batten 1991). In addition, emerging ethical economy, ethical theory of value and ethical social enterprise research (Arvidsson 2016; Bull, et al. 2010) justifies adding “ethical capital” to the digital market infrastructure and stakeholder network that mediates macro and micro domains. Thus, Bourdieu’s four forms are expanded into ten (10) capital flows around a wheel of externally oriented meso-market enablers.
Meso Enablers as Micro Company Mediators
Micro domain mediation is performed by internally oriented meso-market enablers.
They comprise a ring of resource portals that is situated inside the meso domain capitals at the outer boundary of the internal company environment. These internally oriented meso- market enablers deploy company resources through intermediary networks, chains, channels, agencies, alliances, infrastructure, and stakeholders defined as “publics and partners” within the “task environment” (Middlebrook 2014; Kim, Ni, and Sha 2008).
Although the widely cited “McKinsey 7S Model” incorporates many of the “hard” and
“soft” factors that mediate micro domain planning (Channon and Caldart 2015; Waterman 1982; Waterman, Peters, and Phillips 1980), it primarily addresses criteria for analytical decision making (formulation), rather than the cache of actionable management resources deployed (execution). Still, the strategic purpose of McKinsey’s 7S Model is congruent with the company linked ring of meso enablers described here.
These meso-market enablers are referred to as the “M’s of Management,” for “internal (task) environment analysis,” “enterprise resource planning,” and accounting “resource audits” (Pitcher 2018; David and David 2016; Rostamzadeh and Sofian 2009; Tomblin and Maheshwari 2007; Hill and McShane 2006). They are also directly applicable to digital market strategy (Hanlon 2019). Ranging from a core ‘5Ms’, or standard ‘7Ms’, up to an expanded ‘9Ms’, as many as fourteen (14) different “Ms” can be found in varying
combinations. Table 3 lists the “available” 14Ms from the literature on the left, and the “actionable” ‘10Ms’ meso enablers designated for the proposed DDMS model on the right.
Nine of the resulting ‘10Ms’ address micro company mediators that are already in the management literature. The tenth ‘M’ for morality contributes a meaningful enabling capacity for ethics and CSR which has not been directly articulated before. Porter and Kramer (2011, 2006) established the “shared value” premise for strategically linking ethics/CSR with business planning to improve competitive advantage. Similarly, the
American Management Association’s (2006) “ethical enterprise” agenda affirms the
attunement of morality with other management ‘Ms,’ for conventional and digital market strategy (Palmer 2015). These ethics, social responsibility, and governance (ESG) thrusts extend Carroll’s (1991) seminal “CSR Pyramid” into a dynamic digital market realm where “collaborative enterprise” (Tencati and Zsolnai 2009) is the norm. A composite Macro and Meso environment diagram is shown in Figure 3.
Importantly these meso intermediaries for the micro company help to plan traditional as well as digital strategy. An expanding proportion of physical resource processing is becoming intricately interwoven with digital appliances and applications (Woodside and
Sood 2017; Ding and Jiang 2014; Roberts and Zahay 2012), within an “online to offline” (o2o) convergence of economic exchange and electronic commerce through the “internet of things” (IoT). Moreover, both customers and competitors are external micro components of the digital and traditional market machinery. Yet, because they are directly engaged with the marketing strategies of digital/traditional enterprises, customers are framed within the internal target market triangle of micro domain objectives and opportunities (Kotler and Keller 2016; Blacker, et al. 2011; Kennedy, Goolsby, and Arnould 2003; Johnson 1998; McKitterick 1957) Conversely, direct engagement with competitors for market advantage, frames them in inverse triangular opposition to digital enterprise objectives for avoiding
competitive forces’ threats. (Cusumano, Gawer, and Yoffie 2019; Barney 2014; Burns and Warren 2008; Ries and Trout 1986; Porter 1980).
The micro-environment domain is divided into two symbiotic zones for the internal company and external customers (B2C & B2B) – with an opposing external competitor territory. The primary aim of micro-market engagement is “value co-creation” between internal company strategy execution and external customer satisfaction experiences (Smith and Colgate 2007; Prahalad and Ramaswamy 2004). Usually, marketing system frameworks arrange the company’s strategic marketing functions around a target market customer bullseye (Perreault, Cannon, and McCarthy 2019; Kotler and Armstrong 2018), but customers are not revealed as an intricate interactive entity for value co-creation. Those static customer frameworks deprive digital market strategists of an important system component for mapping tendencies (nature) and planning alignment (navigation). Instead, the proposed DDMS model represents the customer’s digital market considerations using the adroit theory of perceived risks (Conchar, et al. 2004; Brooker 1984; Taylor 1974; Bauer 1960). As a result, digital market engagement becomes a compatible alignment among the company’s internal micro ‘10Ms’ functions guided by strategic direction, and the customer’s external micro risk profile, as well as opposing micro competitive forces.
Customer Satisfaction Experience as Risk Choices
Customer satisfaction is achieved through strategic engagement with the configuration of risk profiles used to analyze target market segments. Importantly, the perceived risk construct efficiently and elegantly captures the multiple variable relationships advanced to explain digital customer interaction with companies/competitors, as well as technology interfaces. The theory of perceived risks has high credibility in marketing, psychology, and economics (Dowling 1986; Derbaix 1983; Bettman 1975; Cox 1967), for academic rigor validity and practical real-world viability. It is equally applicable to individual/household (B2C) and organizational/industrial (B2B) customers for any combination of traditional and digital market exchanges of either goods or services, composed of material or informational content. (Caldwell, et al. 2013; Kim, Ferrin, and Rao 2008; Rao, et al. 2007; Forsythe, et al.
2006; Biswas and Biswas 2004; Hunter, et al. 2007; Forsythe and Shi 2003; Laroche, Bergeron, and Goutaland 2003; Miyazaki and Fernandez 2001; Henthorne, LaTour, and Williams 1993; Murray and Schlacter 1990).
Despite its rich synthesis of customer symbiosis strategies, the risk model is noticeably absent from most digital market models. Clearly, the risks are equally capable of accounting for digital business/marketing strategy aims of customer satisfaction and digital technology acceptance/adoption in TAM, E-TAM, UTAUT, and Self-Service Technology (Venkatesh, Davis, et al. 2016, 2012; Jiyeon and Forsythe 2008, 2007; Van Der Heijden 2000;
Dabholkar 2000, 1996; Davis and Venkatesh 1996; Davis 1989). Significantly, perceived risks are capable of profiling complex buyer decision processes and influences with simplified risk indicators for any market choice. Even the customer’s situational context, social/cultural influences, and individual/organizational characteristics are effectively approximated by the differences in risk profiles. Consequently, a ring of customer risks rotates around the standard five cognitive choice process stages.
Moreover, the simple and adaptable codification of complex choices makes the risks palette ideal for programming B2C and B2B customer decision support systems (CDSS) embedded in devices and market interaction channels to serve as “agents of exchange” (Hendrix 2014; Grenci and Watts 2007; Zang and Pu 2006; Grenci 2005; Lee and Chung 2005; Dholakia and Zwick 2001; O’Keeffe and McEachern 2001; Carter 1997). Leading edge innovations in e-commerce/social-media networks, intelligent software applications, and smart mobile/wearable devices have further transformed customers into “digital beings” ensconced in native sapient environments (Prensky 2001; Negroponte 1995). A plethora of individual and group buying e-commerce websites with smart mobile device access are beginning to alter the decision-making styles and trust expectations of digital market customers around the world (Sharma, 2017, 2016). These extended-self experiences in a digital world are embodied in the “digital self” paradigm for digital market customer engagement (Sheth and Solomon 2014; Pak 2014; Epps 2014). Therefore, digital customer interaction is represented by ten risk indicators. The first four extend original financial, functional, psychological, and sociological risks (Brooker 1984; Taylor 1974; Cox 1967; Bauer 1960). Six risks are added to account for physical harm, information privacy trust, time parameters, spatial preference, ethical prerogatives, and ecological preservation. The resulting set of ten customer risks are fully supported in the marketing literature (Tarabieh 2021; Chen and Chang 2013; Durif, et al. 2012; Lee 2009; Johnson, Sivadas, and Garbarino 2008; Newholm and Shaw 2007; Forsythe, et al. 2006; Harrison, et al. 2005; Conchar, et al. 2004; Mitchell 1999). These ten external customer risks align digital market strategy with the ‘10Ms’ internal micro company functions and ten external meso capital facilitators.
Furthermore, the ring of 10 customer risks is composed within a pertinent matrix of customer choice modes (horizontal axis) and motives (vertical axis). The modes of choice divide risks into individual and collective outcomes, whereas motives divide risks into
extrinsic and intrinsic orientations. This overlaid axis, shown in Figure 4, adds another layer of calibration for digital market strategy.
Company Strategy Execution as Realm Charting
Digital market company strategy execution comprises the corresponding zone within the micro engagement domain. It directs strategic symbiosis with the B2C/B2B customer zone parameters, as well as guides enterprise synergy with internal ‘10Ms’ functions, external meso capital facilitators, and external macro trend forces. Marketing strategy, target market segmentation, marketing mix programs, and electronic commerce customer relationship management (eCRM), and Software as a Service (SaaS), all contribute to digital business planning for the micro domain (Chaffey and Ellis-Chadwick 2019; Jain, Jaiswal and Prasad 2017; Quinton 2013; Varadarajan 2010; Chaturvedi and Bhatia 2001). A myriad of digital business platforms has emerged for delivering digital market value (Sharma 2016). The digital marketing strategy literature highlights the use of decision support systems (DSS) to perform the types of market sensing, expertise accessing, data analytics, and scenario planning required to align this micro, meso, and macro domain dynamics (Chan and Ip
2011; Bharati and Chaudhury 2004; Chen and Lee 2003; Leeflang and Wittink 2000; Little 1979, 1970; Simon and Newell 1971).
The ubiquitous social presence of Internet communication media, with advancements in simulated augmented/virtual reality market experiences make this smart artificial intelligence (AI) embedded DSS systems essential for strategic market engagement by digital businesses (Kraten 2007). Increasingly, company strategy execution relies on digital “marketing dashboards” programmed with DSS capability and ‘10Ms’ intelligence to
directly link with target customers’ digital CDSS risk profiles, as well as digitally synch with meso domain capital monitors and scan macro domain trends, to improve enterprise performance metrics (Krush, Agnihotri, and Trainor 2016; Krush, et al. 2013; Pauwels, et al. 2009; O’Sullivan and Abela 2007; Eckerson 2005; Miller and Cioffi 2004). These strategic practices are referred to as “managing by wire” with “virtual value chains” (Stone and Woodcock 2014; Rowley 2008; Overby, Bharadwaj, and Sambamurthy 2006; Benjamin and Wigand 1995; Rayport and Sviokla 1995; Haeckel and Nolan 1993)
The strategic digital market realm for symbiotic micro-market engagement has been
meaningfully defined as “U-space” (Watson, et al. 2004). It consists of four digital strategy quadrants along the two axes of conscious awareness and physical time/space specificity:
“Node” with Nexus Marketing (high physical time/space context & lower amplified awareness) – Value creation in digital approximations of physical space (e.g., Websites, Blogs, Skype, YouTube channels, Netflix video steaming, etc.)
“Matrix” with Synch Marketing (low physical time/space context & lower amplified awareness) – Value creation in digital realms without physical time/space context (e.g., social chat rooms, multi-user video games, financial trading platforms, online gaming/fantasy sport, supply chain vendor portals, etc.)
“Hyper-Real” with Immersion Marketing (high physical time/space context & highly amplified awareness) – Value creation in vividly experienced digital replications of physical reality realms with unique look/feel unlike corresponding physical realms (e.g., virtual reality, 3D big data analytics platforms, 3D pilot flight simulations, etc.)
“Post-Human” with Transformation Marketing (low physical time/space context & highly amplified awareness) – Value creation in vividly experiences digital transformations of physical reality realms with transcendent look/feel (e.g., cyborg consciousness activated by intelligent wearable devices, smart rooms/spaces with artificial life, supercomputer brain docking stations inducing artificial experiences and transported “tech singularity,” etc.),
Having plotted the future digital market realms, successful micro-market engagement requires a directional guide to effectively navigate these four quadrants for physical/digital market interaction. The “marketing mix” or “4Ps” has performed the strategic role of steering marketing strategy decision making for traditional markets (Borden 1964; McCarthy 1960). Although, the marketing mix has enduring utility, it is becoming less capable of navigating emerging digital market dynamics. Thus, following Hoffman and Novak (1996), this study regards a reformulated digital marketing mix as imperative.
“Therefore, marketers should focus on playing an active role in the construction of new organic paradigms for facilitating commerce in the emerging electronic society underlying the Web, rather than infiltrating the existing primitive mechanical structures.” (p. 45)
Rayport and Sviokla’s (1994, p. 3) seminal “marketspace” article also provides timely guidance for formulating a “new organic” digital marketing mix:
“In a world where the traditional marketplace signposts of differentiation no longer matter, where ‘content’ may not automatically mean ‘product’ and
where ‘distribution’ may not automatically mean ‘physical location’, brand equity can rapidly evaporate; product becomes place becomes promotion.”
Marketspace reality suggests that the “4Ps” elements are obsolete for the digital market’s content-intensive value creation process. Accordingly, Alderson’s (1957) pioneering marketing strategy criteria for product success advance a three-element marketing management paradigm consisting of; (a) prolificacy or fruitful fit within strategic space, (b) permanence or stable fixity within strategic space, and (c) plasticity or adaptive functionality within strategic space. This triangle of value creation vectors is affirmed by:
Kumar’s (2004) “3Vs” marketing strategy approaches; (a) defining value segments,
(b) defining value propositions, and (c) defining value networks.
Ballantyne and Varey’s (2006) “triangulation of value-creating activities,” which specifies “knowledge renewal” (intelligence), “relationship development” (intimacy), and “communication interaction” (interactivity).
Allen, et al.’s (2005) “3Ds” of customer experience; (a) designing the right offers and experiences, (b) developing company capabilities, and (c) delivering value propositions.
Narver and Slater’s (1990) “Market Orientation” triangular model; (a) customer orientation, (b) competitor orientation, and (c) inter-functional coordination,
Lee and Grewal’s (2004) three Internet marketing performance guides; (a) response magnitude (intensity), (b) response domain (process), and (c) response speed (responsiveness).
Figure 5 presents the composite micro-market engagement domain, consisting of a digital marketing mix triangle to guide company strategy execution, and interlocking
inverted competitor company triangle, as well as the ten customer risk combinations for creating strategic value through customer engagement experiences.
Digital business strategy is a challenging endeavor due to the turbulent nature and technology-driven navigation of digital markets. The combined Dynamic Digital Market Sphere (DDMS) model shown in Figure 6 is advanced as an improved planning paradigm that synthesizes and aligns pertinent parameters from the meta-analysis of digital market frameworks. Specifically, the DDMS model accurately depicts the digital market’s domains and dimensions, accounts for its networks of interactive dynamism, addresses the macro- oriented direction of digital transformation, allows strategic adaptation to dialectic agency, and aids visual discovery of strategic opportunities for innovation. Prior digital market mapping (Carter and Parameswaran 2012) is repurposed for dynamic strategic navigation.
The DDMS model’s spherical configuration transcends existing frameworks to impart a holistic macro-oriented ecological pattern for the digital business ecosystem (Brownlie 1991; Bronfenbrenner 1979) that expands beyond the myopic micro/meso scope of both
Moore’s (2016, 2006) “Business Ecosystem” and the “Digital Reality Radar” model of Schallmo, et al. (2107) from Berger (2015) shown in Figure 1. The DDMS model’s more
encompassing holistic digital reality is more aptly captured by Floridi’s (2002) “Infosphere” for addressing computer science (micro) and information ethics (macro). Likewise, the term sphere connotes a unified spatial and orbital realm in continuous motion like the digital market’s accelerating innovation. That dynamic circumference represents the digital
market’s nature in a similar manner as Huber’s (1992, 1997) “Geodesic Network” paradigm for U.S. telecommunications policy planning. As a strategic digital market navigation
instrument, the DDMS reflects the intent of Miles and Snow’s (1995) model for “The New Network Firm,” which embraces the “network economy” and “network paradigm” (Achrol and Kotler 1999; Achrol 1996; Castells 1996), within a spherical planning structure.
On a figurative level, the spherical motif conveys relevant meaning for the digital market’s nature and navigation. Just as the ancient vision of the sky as a celestial sphere
allowed orbital geometric patterns to be charted for nautical navigation on earth, the digital market-sphere enables a clockwork charting of strategic orbits in the three-overlapping macro, meso, and micro domains. In turn, by depicting the digital market’s nature as coordinated circuits, similar to an ancient astrolabe, digital business strategy can use the DDMS model like a compass to navigate the dynamic alignments within and between domains. This micro company navigation of the macro and meso digital market domains embraces an open systems view of turbulent trends to “strategically maneuver” by proactively attuning to the cycles of change (Zeithaml and Zeithaml 1984).
On a functional level, the spherical design distills meta-analysis parameters and affirms Bharadwaj, et al.’s (2013, p. 471) “Digital Business Strategy Model” for assessing “the next generation of insights.”
“We identify four key themes to guide our thinking on digital business strategy and help provide a framework to define the next generation of insights. The four themes are (1) the scope of digital business strategy, (2) the scale of digital business strategy, (3) the speed of digital business strategy, and (4) the sources of business value creation and capture in digital business strategy.
The DDMS model establishes a holistic macro-orientation scope for digital business strategy to sense and respond to environmental turbulence. The scale of digital business strategy is expanded with meso-enabling parameters to mediate both macro forces
(stakeholder resource ‘10 capitals’) and micro functions (strategic company ‘10Ms’). The
speed of digital business strategy is enhanced by embedding dynamically aligned micro, meso, and macro domains/dimensions with networked patterns for adaptive agency. The sources of digital strategy value creation/capture are enriched with discovery-driven innovation from dialectic patterns that provide visual serendipity and versatile spontaneity.
Sources: Schallmo, Williams, and Boardman 2017, “Digital Transformation of Business Models,”p.9; From Roland Berger 2015, “The Digital Transformation of Industry,” figure titled “Drivers of Digitization,”p.20.)
The combined DDMS model shown in Figure 6 provides an improved representation of the digital market nature, as well as insightful digital business strategy navigation of digital market relationships. Moving from the outside-in, a series of design alignments in the
digital market’s architecture are revealed. First, there is an inherent logic in the causal tendencies of macro domain trends within digital market conditions. Whereas social-cultural forces hold the dominant sway in traditional markets, technological forces are the primary
source of digital market disruptions. Conventional wisdom has been to monitor technology industries and innovations, but the accelerating pace of change requires building strategic alliances at the basic and applied research level from which the proprietary knowledge for new tech is derived. This ‘tech-knowledge’ is found in basic science labs, academic centers, and global consortia – including intellectual property patent and copyright filings. This type of investigation has historically been the purview of legal staffs in medical or advanced technology industries. But the digital market will necessitate executives and mid- level managers getting in the basic and applied research trenches.
Equally, traditional markets are driven by demographic trends because population forecasts can be translated into significant demand forecasting advantages. Yet, digital markets inherently couple ecological resources and climate patterns with technology development and deployment. This profound coupling is coined as “Digital Sustainability” (Osburg and Lohrmann 2017), because digital market ubiquity (transaction networks) and fluidity (transvection knowledge) can dramatically transform the global potential for ecological preservation, as defined by the UN 2030 Sustainable Development Goals.
A pervasive Digital Sustainability movement recognizes the imperative of
integral digital business and society strategies for navigating the digital market’s nature, as well as to nurture nature with sustainable digital market strategy. For that reason, the DDMS model purposely aligns adaptive ecological parameters in the
macro (ecology), meso (natural capital and mother nature ‘M’), and micro (ecological customer risk) domains. Digital Sustainability scholars affirm this symbiotic mapping of the digital market and ecological milieu to assert shared strategic ethical stakeholder aims, collaborative private/public policy technology innovation alliances, and to actualize company’s green marketing beliefs with digitally facilitated conscious consumption behaviors (Soarviero and Ragnedda 2021; Diez-Martin, et al. 2019; Lock and Seele 2017).
“We are starting to understand sustainability from an ecological perspective but need to learn to also understand its meaning for humans, in an
increasingly digitalized world.”
(Engelsleben, in Preface of Osburg & Lohrmann 2017, xi),
So, for example, the DDMS model enables digital business strategists to chart the macro domain reliance of advanced technology on natural resource ecology material extraction and mining of rare earth metals for critical components, as well as to fabricate synthetic signal conducting substances. Moreover, the deployment of digital services and physical services requiring digital network/applications support must be configured compatibly with topographical smart-cell towers and meteorological satellite patterns. These are a few of the strategic insights for harnessing the causal tendencies in the new environmental order of digitally transformed macro domain trends.
Next, the DDMS model moves inward to the array of meso-market domain enablers. They’re circumferential placement resembles orbiting satellites, filtering the conditions of space to facilitate advantages on earth. So, the mediating meso domain enablers’
relationship between macro domain’s sources of seismic opportunity/threat and the micro domain’s selective strengths/weaknesses should recall the sensing capacity derived from SWOT analysis (Nixon 2010; Watkins 2007; Valentin 2001; Piercy and Giles 1989).
Typically, SWOT analysis is done from the firm’s perspective. But the outward expansion of digital market ubiquity and domain confluence created by fluidity requires an outer layer as an operational staging area to buffer the ripple effect of macro domain trends. Thus, by aligning meso domain enablers with micro domain ‘10Ms’ functional portals, a strategic SWOT/TOWS analysis can be conducted by extending internal company strengths/ weaknesses to the relevant ‘capital’ facilitators for each strength/weakness. This type of agile contingency planning adapts organizational contingency theory (Ruekert, Walker Jr., and Roering 1985) to digital market ubiquity and fluidity dimensions.
Moving further inward to the micro-market engagement domain, an inwardly focused strategic orchestration of meso-market enablers can be visualized. The synchronized planning paths for aligning the eight meso ‘capital’ facilitators, ‘10Ms’ organization portal functions, and eight customer risk palettes is evident. Of course, each of these planning schemas contains features which can be analyzed and applied in multiple combinations – not solely for the path alignments highlighted here. Still, this strategic alignment of meso, company, and customer features is probed for competitive advantages and value creation.
Another alignment path involves temporal capital, the company market function, and the customer’s temporal risk. Concisely, the strategy inference here relates to strategic market windows that are created for customers to experience time freedom or fulfillment utilizing meso domain lifestyle and leisure opportunities across commercial, civic, and community spheres. In a nutshell, the strategy of digital content branding of external loci experiences (e.g., trade shows, distinctive commercial districts like garment or flowers, public parks, neighborhood cultural centers, family farms, etc.)
Now, moving to the innermost strategic pattern of digital market relationships, the symbiotic company/customer micro engagement can be examined. Besides the
compatibility between the company’s ‘10Ms’ and the customer’s eight risks, an essential strategic dialectic can be discovered for the digital marketing mix and customer risks. The intelligence arc analyzes customer risks profiles to identify potential for fruitful fit
(“Prolificacy”) and long-term loyalty (“Permanence”). The intimacy arc uses aesthetic affect and emotional empathy to adapt the risks profile analysis (“Plasticity”) to the
customer’s digital/physical market journey. The interactivity arc opens the company to
embracing customer ownership through flexible digital platform collaboration (“Plasticity”) for co-creating future value fitting (“Prolificacy”). This cycle of micro-market domain engagement evolves into strategic customer relationship management.
Ultimately, conclusions for the meta-theoretical analysis can be derived from the affirmation of four research propositions. Evidence is presented to support the wide variation in existing digital market frameworks, with respect to their holistic depiction, visual interactive dynamism, directional orientation/flow, individual factor/subfactor dialectic agency, and overall capacity to aid scanning/sensing discovery. The earlier discussion of meta-analysis findings examines the range of design parameters within a representative sample of frameworks composed for different digital market purposes and from diverse academic fields of study. Those findings are then used to advance an improved model. Thus, the DDMS model advances valid and generalizable parameters to improve scholarly research and strategic results.
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Panel 2 | Meta-Theoretical Analysis Evaluation Criteria | |||||
Framework | Framework Diagram Image | Depiction | Dynamism | Directionality | Dialectic | Discovery |
II. MICRO Business/Marketing Strategy: Marketing Triangle Functions | ||||||
Kotler (1994) Bitner (1995) Gronroos (2007) Services Marketing Triangle | D
| D
meso/macro | D
| D
| D-
| |
Friedman (2002) Go-To-Market (GTM) Strategy Triangle | D
| D
| D
| D
| D-
| |
Kennedy (1997) 3Ms Marketing Triangle | D
| D
| D
| D
| D-
| |
Ballantyne & Varey (2006) Value Creation Activities
(interactivity) | D
| D
| D
| D
| D--
| |
Additional Marketing Triangles
| D
| D
| D
| D
| D-
| |
Panel 3
Framework Framework Diagram Image
Meta-Theoretical Analysis Evaluation Criteria
Chaffey & Ellis-Chadwick (2012)
Traditional/Digital Business Environment
B+
holistic context
high macro factor detail w/o demog & ecology
low micro/meso detail
no company strategy & customer profile
B+ B
* medium-high micro/ * micro org. (in-out) vs. meso factor interaction macro orient
* good micro fluidity with * no strategy function network/node interaction direction, or macro forces & macro factor influence * holistic system span
B
*medium micro/meso agency w/o macro interaction
* no company/mktg alignment/adap customer p
Broekhuizen, et al. (2021)
Digital Business Model Flow Chart
C+ D+
hewn micro context * low/med micro strategy * micro w/limited macro outcomes interaction 1-way process ma
high micro factor detail * medium micro fluidity w/digital company strategy * no macro/meso str
medium customer profile process input dy
no macro/meso factors * low netwo
customer & macro/meso pattern roles not shown as multiple ou interactions with company
Kannan & Li (2017)
* hew m
Digital Marketing Framework
Watson, et al. (2004)
Uber (“U”) Commerce & Space (strategy matrix)
Panel 7
Framework
Meta-Theoretical Analysis Evaluation Criteria
Framework Diagram Image
McLeroy (1988) Social Ecology Model
Bronfenbrenner (1979) Lee & Kotler (2015) Kotler,et al. (1991)
Kotler/Zaltman (1971)
B-
fully holistic 3-domain context, w/boundaries
low visual detail of domains/factors/items
C
C
* medium aggregate & indiv * neutral domain
D
* low agency interaction to
interaction for domains/factors medium fluidity across
* no company/mktg strategy domains/factors
functions & customer profile items
* no network/node interaction flow
orientation direction
medium direction path across domains/factors
low company/mktg strategy flow guidance
holistic system span
adapt/align domains/
-- lacking detail
low comp
no cu
Brownlie (1991)
B-
C
* fully holistic 3-domain * aggregate circular *
Environmental Analysis & Forecasting
context w/factors flow/interaction w/o
high visual detail indivual factor representation of interaction w
macro/meso/micro across d
no company strategy *me or customer profile
Yun & Liu (2019)
B
Quadruple Helix Open Innovation Model
(Partial Dia
* holistic mar
Van Veldhoven & Vanthienen (2021)
Business, Technology, Society Digital Transformation Framework
Actionable Meso-Market Enabler “Ms”
Money
Management (Mission, Methods, Measurement)
Make-Up
Materials (Machinery, Maintenance)
Members (Manpower)
Markets
Media/Message (MIS – tech conduits/content)
Moments (Minutes)
Mother Nature (eco-environment)
Morality – ethics/CSR (No prior “Ms” literature)
Available Strategic Management “Ms”
Money
Management
Make-Up
Materials
Machinery
Members/Manpower
Markets
Methods
Measurement
Minutes
Mission
Management Information Systems (MIS)
Maintenance
Mother Nature