- Frontiers of Business Research in China

Transcription

Front. Bus. Res. China 2016, 10(1): 115–148
DOI 10.3868/s070-005-016-0006-7
CASE STUDY
Chunyan Wang, Qinghong Yuan, Lin Chen
The
Personnel
Earthquake
Continuum:
Consequences of Collective Turnover — A Case
Study of Qidian Founders’ Collective Turnover
Abstract Unlike previous studies that have primarily focused on the causes and
processes, this research emphasizes the consequences of collective turnover.
Starting from a literature review, we use event chains to explore the
consequences of collective turnover. Based on the case study of the Qidian
founders’ collective turnover, we build a holistic theoretical framework to show
the dynamics and continuity over time, influenced by the complexity of context.
Our main conclusions are as follows: (1) collective turnover has a cascade effect,
causing a series of secondary and derivative events, (2) collective turnover has
both proximal and distal impacts on human capital flow, operational performance
and financial performance, (3) whether or not a collective turnover has a positive
or negative effect depends on the context factors. An event chain perspective that
extends collective turnover theory and organizational behavior theory is used. We
advocate for an integrate understanding of the consequences of collective
turnover. In addition, this research will provide practical, instructive policies to
intervene in collective turnover.
Keywords collective turnover, event chain, human capital flow, operational
performance, financial performance
1
Introduction
Turnover is an important organizational phenomenon that occurs frequently,
especially in high-tech, internet and emerging industries. For instance, in 2013,
seven key designers from BlackBerry 10 left the company to found a new design
Received July 16, 2015
Chunyan Wanga (), Qinghong Yuanb, Lin Chenc
Business School, Nankai University, Tianjin 300071, China
E-mail: [email protected], [email protected], [email protected]
116
group called Topp, more than 20 members of Qidian online literature website (起
1
点中文网 ) moved to Tencent Literature (腾讯文学), and more than 100 people
left Far Eastern Leasing (远东租赁) for Ping An International Financial Leasing
( 平安国际融资租赁 ). Turnover research has moved beyond investigating
individual level “atomic” turnover (characterized by occasional, independent and
individual decision-making), toward examining primary antecedents, process
mechanisms and consequences of collective turnover at the unit level. Collective
turnover is like a “personnel earthquake” in an organization, with the earthquake
and following aftershocks having significant influence on the firm. The
consequences of collective turnover has therefore become an important research
topic.
Researchers have addressed collective turnover; however, existing studies lack
the necessary understanding of the concepts and theories at the unit level. An
explanation for the discrepant findings in the extant turnover literature is
individual-collective partial isomorphism (Ployhart and Moliterno, 2011; Nyberg
and Ployhart, 2013), as most studies still rely on individual-level turnover
theories and assumptions (Hausknecht and Trevor, 2011). This suggests that
researchers cannot assume that findings from one level generalize to other levels
(Ployhart and Moliterno, 2011). One example illustrated by Hausknecht and
Trevor (2011) is that individual-level turnover research suggests that involuntary
turnover positively affects performance, but collective turnover research suggests
that all turnover is negatively related to unit performance, because of
coordination disruptions and erosions of the climate (e.g., McElroy, Morrow and
Rude, 2001). It is inappropriate to generalize individual-level findings to the unit
level by simple additive aggregations, especially for collective turnover.
Dissatisfaction experienced by individuals who are part of a group may, under
some circumstances, lead to group processes (Bartunek, 2009), and then lead to
collective turnover intention and exit behavior. In the escalating interaction
process, there exists complicated cognitive, emotional and relational interactions
among the members of the group. Collective turnover behavior cannot be
1
Qidian is an online original literature platform under Shanda Literature before Shanda was
acquired by Tencent. It is regarded as the inventor of the business model that is widely applied
by almost all online original literature platforms in China. Starting as an amateur writers union,
Qidian was launched in mid-2002 and began charging for premium content, .02–.05 yuan per
thousand Chinese characters, in late 2003. It shared revenues with writers from the very
beginning. It was acquired by Shanda in 2004 and reportedly turned a profit in 2006.
The Personnel Earthquake Continuum: Consequences of Collective Turnover
117
equated with a simple sum of individual departures. Its antecedents, process
mechanisms and consequences are complicated and cannot be predicted. A new
theory for collective turnover must be developed.
Most studies use turnover rates as the measurement of collective turnover,
which is effectively the sum of individual turnover decisions (Hausknecht and
Trevor, 2011; Shaw, 2011). In the studies reviewed by Hausknecht and Trevor,
25 percent did not report how to measure collective turnover, and 65 percent
used separation rates, but did not capture valuable information regarding the
timing of leavers, the proficiencies of remaining members, or the distribution of
leavers across positions. Nyberg and Ployhart (2013) indicate that, at the
collective level, measurement may be better served by focusing on the quality
and quantity of the mix of collective turnover. A more detailed report of the
relevant factors such as leavers’ characteristics or the distribution of leavers
across positions is necessary.
Further analysis of the consequences of collective turnover is still needed.
Moreover, while existing research has examined the negative effects of collective
turnover (e.g., McElroy, Morrow and Rude, 2001; Simons and Hinkin, 2001;
Kacmar, 2006), few have set out to examine its potential benefits. As negative
effects may be offset by positive effects, researchers may observe no relationship
(e.g., Detert, Trevino, Burris and Andiappan, 2007; Guest, Michie, Conway and
Sheehan, 2003; Sowinski, Fortmann and Lezotte, 2008). Potential positive
consequences of turnover include greater innovation, increased adaption and
flexibility, reduced worker conflict, greater promotional opportunities,
accelerated career growth, greater inter-firm cooperation, reduced labor costs,
and better long-term economic growth ((Hausknecht and Trevor, 2011;
Muchinsky and Morrow, 1980; Staw, 1980). By addressing the positive and
negative consequences of collective turnover in the same study, the precision of
future research will be strengthened, and a more comprehensive understanding
could be provided.
After following the Qidian founders’ collective turnover event for fourteen
months, we analyze the consequences of collective turnover and present a
theoretical framework of collective turnover in this study. With the collective
turnover event as a starting point, we build a longitudinal event chain,
incorporating context and time, and explore the complicated effects of collective
turnover caused by the interactions among leavers, the human capital losing firm,
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the rival firm, and other actors in the organizational field.
We focus on the consequences of collective turnover, which includes both the
horizontal effect—the effects on the organization, industry, rival firms, personnel
that leave or stay, the vertical effect—the impact of the timing of the occurrence
and the chain effect of the incident, and even the individual level effect, which
may be less important in a collective turnover situation. The effects are
complicated, and may not be predictive, or even have an impact on industry
development, possibly expanding the industry boundary. We make three primary
contributions. First, a new perspective to explain collective turnover is used, that
extends collective turnover theory and organizational behavior theory. We argue
that based on event chain theory and existing studies, collective turnover has a
dynamic and cascade effect that causes a series of secondary and derivative
events, having both a proximal and distal impact on human capital flow,
operational performance and financial performance. Second, whether collective
turnover has a positive or negative effect depends on the context, and the
industry environment and industry boundary will enlarge or diminish the
consequences of collective turnover. Third, a longitude single case study
provides detailed information about collective turnover, for a comprehensive
estimate of the collective turnover effects.
2
Literature Review and Theoretical Background
2.1
Consequences of Collective Turnover
To explain the turnover-performance relationship, researchers have relied
primarily on three theoretical perspectives（Park and Shaw, 2013; Heavey,
Holwerda and Hausknecht, 2013). (1) Resource depletion. This perspective is
based on human capital theory or social capital theory and posits that turnover
damages performance because it conveys a loss of firm-specific human capital
(the quantity and quality of knowledge, skills, abilities and other characteristic
(KSAO)) (Nyverg and Ployhart, 2013; Osterman, 1987) and social capital (Dess
and Shaw, 2001; Shaw, Gupta and Delery, 2005). Empirical research generally
supports this argument (Morrow and McElroy, 2007; Hausknecht and Trevor,
2011; Kacmar, Andrews, Van Rooy, Steilberg and Cerrone, 2006). (2)
Operational disruption. This perspective implies that collective turnover disrupts
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established patterns of interaction, creates instability in coordination, and diverts
attention to nonproductive activities (Heavey, Holwerda and Hausknecht, 2013).
Relying on theories of organizational learning and control, Park and Shaw
suggest that compared with organizations with low turnover rates, organizations
with high turnover rates have workforces that lack accumulated human capital,
and therefore replacements can quickly build equivalent capital and rapidly
negate human capital losses, which means an increase in turnover rates from
low-to-moderate levels are more disruptive to organizational performance than
an increase in turnover rates from moderate-to-high levels (Price, 1977; Shaw,
Gupta and Delery, 2005; Park and Shaw, 2013). (3) Cost/benefit. From the
perspective of cost-benefit theories, several studies have found some turnover
benefits organizations by reducing compensation costs, revitalizing the
workforce, and sorting out poor performers (Park and Shaw, 2013). Allen, Bryant
and Vardaman (2010) identify several separation and replacement costs
associated with turnover, such as owed salaries, benefits, accrued vacation time,
interviewing, advertising, and training costs. This view proposes an inverted-U
relationship between turnover rates and performance.
The logic of each theoretical perspective is different, and there are conflicting
conclusions, so more fine-grained research is needed. Based on the resource
depletion view, the proximal effect refers to a loss of human capital, while distal
outcomes capture organizational performance and social capital change. The
operational disruption perspective focuses on process and knowledge chain
disruption caused by position vacancies due to human capital flow. The
cost/benefit perspective considers comparative collective turnover costs and
benefits. A better understanding of collective turnover consequences can be
reached when the three research perspectives are integrated for a comprehensive
and synthetic analysis of proximal and distal, instant and delayed effects.
2.1.1
Proximal and Distal Performance Outcomes
The consequences of collective turnover can be categorize into two broad
categories—proximal and distal (e.g., Heavey, Holwerda and Hausknecht, 2013).
Proximal outcomes signify direct outputs and include increased recruitment
and selection costs (Bluedorn, 1982; Dess and Shaw, 2001; Mobley, 1982;
Osterman, 1987; Price, 1977; Staw, 1980), higher accident rates (Shaw, Gupta
120
and Delery, 2005), longer customer wait times (Kacmar, Andrews, Van Rooy,
Steilberg and Cerrone, 2006; Peterson, Luthans, 2006), decreases in customer
service (Hausknecht, Trevor, and Howard, 2009), greater counterproductivity
(Gelade and Ivery, 2003; Kacmar, Andrews, Van Rooy, Steilberg and Cerrone,
2006), reduced manufacturing efficiency (Shaw, Gupta and Delery, 2005), and
absenteeism. For example, Kacmar, Andrews, Van Rooy, Steilberg and Cerrone
(2006) studied fast-food restaurants and report indirect negative effects of both
crew and manager turnover on sales and profits. Efficiency mediates these
relationships such that higher turnover is associated with longer customer wait
times, and longer wait times are associated with lower sales and profitability.
Distal outcomes capture the financial returns (e.g., sales, profits) generated by
the group or firm activities, including reduced profits (McElroy, Morrow, and
Rude, 2001; Morrow and McElroy, 2007; Peterson and Luthans, 2006; Riordan,
Vandenberg, and Richardson, 2005), lower sales (McElroy, Morrow, and Rude,
2001; Shaw, Gupta and Delery, 2005; Siebert, Zubanov, 2009), and lower
revenue growth (Baron, Hannan and Burton, 2001; Batt, 2002). Morrow and
McElroy (2007) find support for a turnover-efficiency-profits mediated model. In
their mortgage bank subunits research, they report that higher voluntary turnover
rates are associated with increased costs per loan and less efficient loan
generation, which in turn are associated with lower profitability. Ton and
Huckman (2008) find negative relationships between total turnover rates
(measured three months before profits) and subsequent store profit margins.
McElroy, Morrow and Rude (2001) find negative correlations between three
turnover measures (voluntary, involuntary, and reduction in force) and same-year
profitability, yet only involuntary turnover remains statistically significant when
controlling for size, location, and service mix. Simons and Hinkin (2001) find a
negative relationship between voluntary turnover rates and gross operating
profits.
2.1.2
Context Factors
The relationship between collective turnover and organizational performance
may be different depending on the context or environment in which turnover
occurs (Park and Shaw, 2013). The context factors help to explain inconsistencies
in the turnover rates–performance relationship in the empirical literature. Several
121
studies find evidence supporting a beneficial effect (Abelson and Baysinger,
1984; Dalton and Todor, 1979; Staw, 1980), and several studies find a curvilinear
effect (Shaw, Gupta and Delery, 2005).
Several context factors are discussed in the literature. Researchers have often
suggested that turnover rates more strongly and negatively affect organizational
performance under primary employment systems (commitment system) than
under secondary employment systems (control systems) (Arthur, 1994; Guthrie,
2001). For instance, Siebert and Zubanov (2009) compare full-time employees
under a commitment system and part-time employees under a control system and
find that turnover rates are more strongly and negatively related to sales when the
turnover occurred in commitment systems. Climate is also an important factor
(Schneider, 1987; Carr, Schmidt, Ford, and DeShon, 2003; Ployhart, Weekley,
and Baughman, 2006). Nyberg and Ployhart (2013) developed the
Context-Emergent Turnover (CET) theory to explain the nature of collective
turnover. They posit that climate moderates the collective turnover–unit
performance relationship, by offsetting or exacerbating the effect of collective
turnover on performance; for example, losing higher-quality employees may lead
to a turnover contagion effect (Felps, Mitchell and Hekmanet, 2009). Also, the
work climate will change as a result of collective turnover and human capital
resource accumulations (Ostroff, Kinicki and Tamkins, 2003; Schneider, 1987).
Nyberg and Ployhart also posit that environmental complexity influences
(moderates) the direct effect of collective turnover on unit performance. For
example, collective turnover will be much more damaging to an intensive
workflow structure (where members must rely on each other, e.g., a surgery team
or a team-based manufacturing organization) than in a pooled workflow structure
(tasks are largely independent, e.g., a box store, such as Wal-Mart, or drivers in a
trucking company) (Shaw, Gupta and Delery, 2005; Nyberg and Ployhart, 2013).
Also other factors like entity size (Hausknecht, Trevor and Howard, 2009),
industries (Datta, Guthrie and Wright, 2005; Shaw, Park, and Kim, 2012), and
region (Ahmad and Schroeder, 2003) will have effects on the relationship
between collective turnover and the consequences.
2.2
Event Chain
In natural disasters (e.g., floods, earthquakes) or emergencies (e.g., SARS, bird
122
flu) or biology research fields, it has been observed that incidents may lead to a
series of secondary and derivative events, which can be called event chain effects.
These chain effects make the event even more complicated.
Seismologist Guo Zengjian (1987) presents the “disaster chain” concept to
mean a series of disasters follows one disaster. The disaster chain is a composite
system that includes a set of disasters where each episode is caused by the
previous episode, or starts with the causal episode followed by a consecutive
series of reactions among episodes and subsystems. The disaster chain exists
because of the interaction of disasters, and the strength of the interactions lead to
these episodes being considered as a single entity (Liu, Xiao, Sui, Zhou and Gao,
2006). Natural hazards are typically used to define the disaster chain, and
researchers generally posit that it is a series of disasters triggered by natural
hazards or ecological environment change (Shi, 2003). Some researchers suggest
that the disaster chain is a phenomenon of disasters caused by a previous disaster
(Wen, 1994). The existing research focuses on the integrity of the disaster chain
taking a more macro perspective to understand the chain relationship.
Furthermore, based on disaster systems theory, the disaster chain is considered to
be an abstraction of the process of a variety of disasters, and contains various
chain relationships in the evolution process (Shi, 2003). The process of the
disaster chain plays an amplification or accumulative role, with the natural
hazard providing the conditions for the evolution of later disasters, and the later
disasters expanding the scope of the prior disaster’s influence (Yin, Wang, Yu and
Shi, 2012). Research into the kinetics of enzyme-catalyzed reactions shows that
in the process of enzyme-catalyzed reactions, a prior reaction product is the
catalyst of a later reaction, and modification reactions will lead to signal
conditioning amplification each time similar to a cascade effect. Ripple and his
colleagues (2014) provide another example for event chains in biology: large
carnivores have substantial effects on the structure and function of diverse
ecosystems, via direct and indirect pathways such that large carnivores may
enhance biodiversity, carbon storage to buffer climate change, and even
regulation of diseases, while a change in large carnivores have cascading
influences on crop damage, stream morphology, and species (e.g., birds,
mammals, amphibians, reptiles and invertebrates) population change. The
disaster chain, enzyme-catalyzed reactions and ecosystem cascade effect reflect a
series of consequences caused by an event, that is, an event chain effect.
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While organizations are dynamic, hierarchically structured entities, significant
events are emergent at every organizational level. However, there has been
relatively little discussion about how events become meaningful and how they
come to impact organizations across space and time (Morgeson, Mitchell and Liu,
2015). It would be an appropriate attempt to analyze the consequences of
collective turnover through the logic of the event chain. Collective turnover is a
“personnel earthquake” in an organization and the consequences of collective
turnover include both instant impacts and secondary and derivative effects. Event
chain theory can help identify the causal or logical relationship of the sequence
of events, and analyze the factors that facilitate the evolution of events, while
also providing an integrated understanding of the consequences of collective
turnover to explain the chain relationship from a macro perspective.
3
Methods
Single case studies can richly and persuasively describe a phenomenon
(Siggelkow, 2007). A single case study consisting of a real-time longitudinal (14
months) study was conducted to describe how and why collective turnover has
event chain effects. A temporal-spatial analysis of the consequences of a typical
collective turnover event can indicate detailed information about change at
different stages (Yin, 1994) and help to capture a complex emergent process. We
examine the details of the case and then introduce a collective turnover
theoretical framework.
We chose the case of the Qidian founders’ collective turnover for the following
reasons. (1) Variation maximization. Pettigrew（1990）suggests that a case study
should be selected for its unique or extreme circumstances, so that such a case
will be helpful to access rich, detailed and in-depth information. This case is
typical and extreme, and is therefore salient for the following reasons. First, more
than 25 persons (out of about 200 writers), consisting of 70 percent of the editors
left, and all went to the same organization (Tencent), amplifying the
consequences. As well, because they were from a wide distribution of positions,
the consequences of collective turnover could be better observed. Second, Qidian
was an industry leader, and the founders who left are those who had built the
criteria and rules of the industry, which makes the event novel, disruptive, and
critical. (2) Specific information available. As the online literature industry in
China is an emerging and specific industry, information referring to the collective
124
turnover event (e.g., the group who left, Qidian and other stakeholder
information) was updated quickly and could be accessed from the internet.
3.1
Data Sources
We collected data from several sources, mainly literature, interviews, and actual
evidence confirmed by multiple sources.
(1) Stakeholder tracking: data on leavers collected from blogs, Weibo (微博),
press statements, posts and replies on Longkong BBS (龙空论坛); rivals’ reviews;
other actors’ data, including the actions of the Qidian and Shanda Literature
Group (盛大文学集团), and actions and views of other employees, readers, and
writers. (2) Network news reports. (3) Public information on the Qidian and
Chuangshi website (创世中文网) (the website founded by the departure group).
(4) Monthly on-line searches for relevant information (5) Secondary sources and
other data, such as industry research reports, and data monitoring of vertical
literature websites by iUserTracker. (6) Interviews with several readers and
online literature industrial professionals.
3.2
Data Analysis
Eisenhardt points out that “it is the connection with empirical reality that permits
the development of a testable, relevant, and valid theory” (1989: 532) and Van
Maanen contends that this type of research “should be empirical enough to be
credible and analytical enough to be interesting” (1988: 29). Thus, as we seek to
tell a story based on the analysis of themes (Dutton and Dukerich, 1991), a story
about how the consequences of collective turnover developed, our thematic
analysis follows the steps described by Miles and Huberman (1994) and used by
Plowman et al. (2007).
Step 1: Using an actors’ summary sheet. We used a summary sheet to record
the main actions and issues of the leavers, the Shanda Literature Group, and
other actors in the online literature industry. A theme was defined as a recurring
topic of discussion and main actions as key events confirmed by multiple sources
that captured the research topic’s central ideas (Dutton and Dukerich, 1991).
Step 2: Creating a complete theme list. A literature review, and the process
used to complete the summary sheets resulted in a list of unique themes and
125
actions. We required that the uniqueness of the themes be identified within each
key event by the original theme coder and the cross-checker but allowed for
commonly identified themes. We coded each identified theme for analysis and
tracking purposes. Following O’Reilly, Chatman, and Caldwell’s (1991) Q-sort
process, we required the categories to be nonredundant, readable, general, and
discriminant. This process resulted in several broad classifications of themes,
including
job
vacancies
filled,
operations
interruption,
satisfaction,
organizational change, service quality, operational performance, financial
performance, and market performance. We then coded these themes into three
main major themes- include human capital flow, operational performance and
financial performance.
Step 3: Construction of timeline. We constructed a timeline of the key events
that happened after collective turnover (Table 1), based on selected BBS data,
newspaper articles and descriptions from key figures.
Step 4: Narrative analysis. Narrative analysis is useful in organizing
longitudinal data, especially data based on a single case with abundant
information (Langley, 1999). Therefore, we recoded the story of the development
of events after the collective turnover behavior happened, by moving back and
forth among events in the timeline, the data, theory and other evidence.
Step 5: Event chain mapping. We drew the consequence chains of the collective
turnover event (Figure 1) according to the timeline and narrative analysis.
Step 6: Validity checks. We relied on multiple sources of data wherever possible
to check the validity of our study. Data was obtained from multiple sources,
including interviews, observations, documents, and secondary sources, data
collected from turnover actors, the Shanda Literature Group, rivals, writers and
editors and other stakeholders involved in the event. Our reporting includes only
data substantiated from multiple information sources. We also used multiple
methods, such as a key event timeline, narrative analysis and visual mapping. For
a final check on the accuracy of our findings, we presented our final story to
other researchers for confirmation of what we had found as well as additional
insights and details. This presentation led to revisions of the event chain mapping
and corrections in some of the details of the event chains.
T1: 2013 Apr.−Jun.
5.14 Formal
appearance of
new TMT.
5.21 New writers’
benefit system.
5.27 Luo is detained.
5.30 Chuangshi in
Tencent
Literature
launched.
T0：2013 Mar.
3.6 Resignation letters.
3.6 CEO Hou internal
mail.
3.11 Shanda Literature
supports Hou.
3.17 Hou publishes
recruitment
information on
Weibo.
3.21 Collective turnover.
3.22 Shanda cracks down
on piracy.
Mar.−Apr. Disclosure of
turnover process
information posted in
Longkong forum, in the
name of the CMFU
(Chinese Magic
Fantasy Union, the
predecessor of Qidian),
seeking approval.
Shanda
Literature
and Qidian
Departure
Group
/Chuangshi
Table 1 Collective Turnover Key Events Timeline
T2: 2013 Jul. −Sep.
7.09 Shanda Literature strategy
press conference.
7.12 Shanda raises about 110
million dollars through private
placements.
7.12 Shanda Literature withdraws
IPO.
7.23 Yuncheng lays off 50 to 60
employees (80%), Yuncheng
and Qidian integrate.
7.27 Shanda literature announces a
new strategic investment in
Xinhuaxinmei (新华新媒)
media company.
8.10 Information in Longkong
forum shows Tencent and
Shanda Reconciliation.
8.10-8.15 Chuangshi terminates
contracts with ten former
Qidian star writers, Luo
released.
9.3 Chuangshi vip channel online,
improve subscription price.
(To be continued)
12.17 Chuangshi and 17K strategic
cooperation.
2014.4 Wu officially appointed Tencent
Literature CEO.
2014.4 Former famous Qidian star writer
Maoni (猫腻) joins Chuangshi.
12.12 CEO Hou turnover.
12.25 Shanda Literature and the
Shanghai Institute of Visual Arts
set up first online literature degree
in China.
12.25 Qidian market share declines.
T3: 2013 Oct. −
2
Literature
Industry
T0：2013 Mar.
T1: 2013 Apr.−Jun.
4.27 Baidu Duoku
literature test.
5.10 Subsidiary of
Shenhua group
buys Chaoliuyc
(潮流原创)
literature
website.
T2: 2013 Jul. −Sep.
7.1 Sina Weibo reading site comes
online (book.weibo.com)
7.1 Baidu Duoku automatic sign
system comes online.
Jul. Former vice president Duan
turnover, moves to Duoku.
8.14 Baidu acquires all shares in 91
Panda Reading mobile app (91
熊猫看书) for USD1.9 billion.
T3: 2013 Oct. −
10.11 People website (人民网) acquires
69.25% share in Kanshu (看书网)
for CNY249 million.
10.28 Sina original (新浪原创) launches
male/female channels.
10.30 17K founds online literature
college, Mo (莫言) becomes
principal.
12.27 Baidu acquires all shares in
Zongheng.com (纵横) for
CNY191.5 million.
(Continued)
128
Figure 1 Qidian Collective Turnover Continuum Map
4
Consequences of Collective Turnover
The complicated effects of collective turnover are amplified by the interactions
of leavers, the human capital losing firm, the rival firm, and other actors in the
organizational field, and the context within which they interact. Every time two
actors interact, the actions of one has consequences for the other, whose
responses feeds back information to the first actor, who then responds; the result
is a continuous circular loop, or what Weick (1979) called a “double interact.”
Through data analysis, we observed three event chain effects caused by
collective turnover: (1) Human capital flow. Proximal outcomes include job
vacancies filled by Shanda Group assignment, or through promotion, or
recruitment, and distal outcomes the management and control power shifts of the
top management team (TMT), joint turnover, and the impact on intervenor career
development. (2) Effects of disruption on operational performance. Proximal
outcomes include disruption in operations and service quality, and complaints
from writers, while distal outcomes include organizational change such as TMT
change, institutional change, strategic change, and structural change. (3) Effects
on financial performance. This includes replacement costs due to human capital
loss, and market share decline caused by the movement of writers and readers.
Proposition 1. Collective turnover has a direct influence on, and will lead to a
series of secondary and derivative events. Collective turnover will influence
human capital flows, operational performance, and financial performance.
4.1
129
Human Capital Flow
4.1.1
Proximal Outcomes: Job Vacancy Chain Effects
After departures occur, as human capital flows out, the organization faces the
problem of employee replenishment to fill vacancies. An individual agent,
whether organism, neuron, or firm, depends on the context provided by the other
agents. “Roughly, each kind of agent fills a niche that is defined by the
interactions centering on that agent. If we remove one kind of agent from the
system, creating a ‘hole’, the system typically responds with a cascade of
adaptations resulting in a new agent that ‘fills the hole’. The new agent typically
occupies the same niche as the deleted agent and provides most of the missing
interactions.” (Holland, 1995, P. 27)When collective turnover happens, creating
job vacancies, organizations adapt in different ways to fill these“holes”, which
also leads to human capital flow. In fact, the flow means the job vacancy
chain—building block can be used for understanding many social and economic
phenomena that involve mobility and inter-dependence. When some employees
leave, their positions become vacancies, and provide other employees with
promotion opportunities. When those employees are promoted, it results in other
vacancies in the organization, that is, there is a flow of vacancy, and the vacancy
could be filled in different ways (see Table 2).
Table 2
Job Vacancy Chain Effects After Collective Turnover
Vacancy
Level
High level
Supplementary
Assignment
Promotion
Recruitment
Promotion
Middle level
Low level
Recruitment
Recruitment
Effects Chains
Control rights changeÆorganizational structure
integrates
Top manager’s career development, vacancy
transmission Ænew vacancies
Culture adaption, vacancies filled
Employees career development, vacancies transmission
Ænew vacancies
Vacancies filled
Vacancies filled
Qidian adopted three ways to fill vacancies: assignment, promotion, and
recruitment. After the collective turnover event all the top management team
vacancies, including the positions of CEO, general manager and vice-general
130
manager were all filled from assignment from the Shanda Literature Group,
which improved the parent company’s control rights over Qidian. Another three
TMT vacancies were filled through promotion, and one from hiring from outside
someone with occupational experience. As the table indicates, human capital
flow caused by collective turnover facilitated the transfer of control from the
Qidian founders’ team to Shanda Literature.
The middle level vacancies were filled by employee promotion, and the
vacancies left after promotion were filled by recruitment. Hou (侯小强) published
recruitment information in his Weibo on March 17th, and received thousands of
resumes in one day. According to media reports, more than 200 persons were
interviewed, and 30 of them were hired by Qidian. Four remaining editors were
promoted to the position of team leader.2
4.1.2
Distal Outcomes: Effect of Power Adjustment
There is a divergence of ownership-control rights in this organization. Qidian
development was primarily directed by the founders’ team before the collective
turnover event. Shanda attempted to gain control by sending in their own top
managers, by creating the website Yuncheng (云中书城, www.yuncheng.com),
and business divestitures. With the increase in wireless revenue, the conflict of
interest between the founders and investors was intensified. The departures
provided an opportunity to Shanda to acquire control rights by replacing the top
management team, and to stop putting resources into Yuncheng. A distal effect
was a reduction of 50 to 60 (80 percent) employees of Yuncheng. Yuncheng and
Qidian were fully integrated on 23th, July, 2013. This indicates that, when there
is collective turnover of founders, investors get an opportunity to gain more
control, and then they may engage in some structural or strategic adjustments.
4.1.3
Distal Outcomes: Impact on Intervenor
The intervenor in collective turnover events will also be influenced. In this case
Hou, a professional manager, CEO of Shanda Literature, played the role of
intervenor. He sent an internal mail when the organization received the
2
http://web2.iresearch.cn/media/20140815/236525.shtml
Notes. Data collected from March 2013 to May 2014.
Source：Focus organizational website public information, news reports, and relevant persons’ Weibo.
Name
Hou XQ (Dec. 2013
Shanda Literature CEO
Hou XQ
Shanda Literature CEO,
turnover)
Shanda Literature
Shanda Literature
Wu WH (founder, Mar.
President, Qidian Board
President,
Qiu WY(Assignment)
2013 turnover)
Chairman
Board Chairman ,CEO
Shanda Literature Vice
Shang XS (founder, Shanda Literature vice
Cui W (Assignment)
President, Qidian GM
Mar. 2013 turnover)
president, Qidian GM
Lin TF (founder, Mar.
Executive Deputy GM
Qidian Deputy GM
Si JQ (Promotion)
2013 turnover)
Deputy GM ,
Hou QC (founder, Mar.
Zhou
YM
Qidian Deputy GM
Director of Content Center 2013 turnover)
(Assignment)
Deputy GM ,
Luo L (founder, Jan. Manager of Publishing
Director of Publishing
Ye J (Recruitment)
2013 turnover)
Center
Center
Director of Operation
Zhu J (Mar. 2013
Center
turnover)
Vice Director of Operation Yang C (Mar. 2013
Center
turnover)
Director of Technical
Si JQ
Qidian Executive Vice
Center
Chen C (Promotion)
Chief Editor
Vice Chief Editor
Chen C
Qidian Executive Vice
Vice Chief Editor
Liao JH
Liao JH (Promotion)
Chief Editor
Position
Position
Name
Qidian TMT-After Collective Turnover
Qidian TMT-Before Collective Turnover
Table 3 TMT Members Change
Name
Wu WH
Cheng W (Assignment)
Shang XS
Zhang R (Assignment)
Luo L
Zhu J
Hou QC
Yang C
Zhou BL (Former Qidian
Editor)
Position
CEO
Board Chairman
President
Executive Vice
President
Vice President
Vice President
Vice President,
Vice Chief Editor
Chuangshi Chief
Editor
Chuangshi Vice
Chief Editor,
Director
Tencent Literature TMT
132
resignation letters, in which he approved the turnover and reminded leavers “to
obey the business ethical spirit.” To some extent, this action aggravated the
contradictions, and the turnover and hiring happened in one month. The
interactions of these actors involved in collective turnover amplified the
consequences of collective turnover and affected the actions of others in the
system. In this case, it developed along the path of “collective turnoverÆQidian
cracks down on piracyÆTMT adjustmentÆChuangshi in Tencent
foundedÆShanda Literature strategy adjustmentÆShanda Literature IPO
withdrawal Æinvestor and professional manager control conflictÆ Hou’s
turnover.” It is a challenge for the intervenor to break the consequences of
collective turnover. The way the intervenor deals with the collective turnover
event, and the process of how events evolve all have direct and indirect effects on
the intervenor’s own power and career in the organization.
Hou’s rapid response to the collective turnover event was supported by Shanda
Literature, which aggravated the contradictions, and shocked the remaining
employees. One of the founders, Luo (罗立), commented, “Even without any
retention, (Hou) cannot wait to take over.” As leavers posted in the Longkong
forum seeking support, adverse rumors about Hou spread on the internet. As well,
there were different views of these leavers, whether they were “traitors”
(voluntary turnover) or “cleared” (involuntary turnover). These interactions
caused sympathy for the leavers from Qidian’s remaining employees, industry
insiders, writers and readers. Due to weak non-competition laws in China, and
the disagreement of employees, writers and readers about the treatment of the
employees who left, there was support for the group of employees who left to
reenter the online literature industry.
The intervenor will be affected by his actions and interactions with others, and
may be held responsible for less than ideal interventions or amplified
consequences, or assume the risk of collective turnover consequences. According
to another professional manager who had experienced a collective turnover event,
an intervenor could also benefit from it, by obtaining a superior’s approval,
gaining more power, and becoming embedded more strongly in the organization,
understanding the industry better, and also acquiring career development.
“In the afternoon of March 6th, when they received CEO Hou’s mail in the
company mailbox or saw media reports, my colleagues were shocked.…Nobody
133
could imagine so soon.… what I can say is, I am very sad, never had been so
confused. ”
—An employee of Qidian, “A log had no place to put,” March 8th, 2013
“I always feel sympathy and understanding for the departed group, not
because of identity or affective identity, but more because I’m worried about the
industry development. …… referring to Shanda Literature and Hou, I had talked
about his contribution to expand the literature industry, but I still think that he
(or Chen, chairman of the board of Shanda) must take unavoidable responsibility
for the Qidian founders collective turnover.”
—17K Literature founder, general manager Ying Liu, March 2013
Proposition 2. Collective turnover will cause a vacancy chain, collective
turnover is positively related to human capital flow within the organization, and
collective turnover is positively related to the promotion of remaining
employees.
Proposition 3. Collective turnover that includes founder(s) will lead to TMT
adjustment, and right of control adjustment.
Proposition 4. Collective turnover has an effect on intervenor career
development. Context will moderate the relationship between collective turnover
and intervenor career development.
4.2
Effect on Operational Performance
Context-emergent turnover (CET) theory suggests collective turnover is the
quantity and quality of depletion of human capital from the unit. As described by
adapting Dierickx and Cool’s (1989) bathtub metaphor, the different between the
speed of depletion and replacement will influence the organizational human
capital resource stock. Even a key employee’s departure will have great influence,
and a mutual collaboration group turnover is not just a simple “flow,” as it can,
for instance, bring network disruption effects, impact the firm’s internal and
external social capital, change the social network, as well as contribute to
knowledge, information, and work process disruption.
There are inconsistencies in previous research about the consequences of
collective turnover. Consideration of proximal and distal consequences may
134
provide a new perspective. Collective turnover will damage the
intra-organizational structure, through the disruption of the knowledge chain and
the process chain, and the proximal outcomes, such as operations interruption, or
a decrease in customer service, is inevitable. But in the long term, it may provide
an opportunity as a source of flexibility and change. In the case study of Qidian
founders’ collective turnover, we conclude that the operational performance
effects chain is “collective turnover Æ human capital flow Æ operations,
knowledge disruption Æ service quality decline Æ writers’ dissatisfaction,
productivity decline Æ customer complaints Æ writers, readers joint mobility Æ
institutional change Æ structural and strategic change.”
4.2.1 Proximal Outcomes: Remaining Employees’ Higher Job Demands,
Operations Disruption, Service Quality Decline
Focusing on job demands highlights the expectations of the remaining unit
employees after departures occur, as the vacancies and the fact that replacement
hiring is often subject to delay, or when new members are hired, working
protocols and relationships can initially be less effective (George and
Bettenhausen, 1990). The remaining unit employees face additional per-person
work requirements, and the amount of work and time required increases. Reilly,
Nyberg, Maltarich and Weller (2014) explore turnover rates and patient
satisfaction with a sample of 12 nursing units in a large hospital over 72 monthly
observations. They show that managers can actively influence job demands when
employees leave by reducing the amount of assigned work so that the remaining
employees do not face additional per-person work requirements, (e.g., by
admitting fewer patients). Alternatively, units can maintain prior levels of output
requirements and increase the work burden on the remaining employees. Qidian
could not reduce the amount of assigned work, and the remaining editors needed
to repair and maintain the linkages with the writers served by the editors who left.
Therefore, in this situation, the work burden on the remaining employees
increased, and the service quality declined.
The pressure on the remaining employees was extreme due to the following
characteristics of the turnover event: (1) Quantity. More than 27 (70 percent) of
the employees left at the same time. (2) The departing employees were part of
different hierarchies. This created a more complicated context and was a big
135
shock to the remaining employees (e.g., this is illustrated in “A log had no place
to put,” and Liao’s (廖俊华) Weibo on March 5th, 2013, “I nearly can’t hold on, I
really want to cry…”). Because many supervisors left, operations were ruptured
and it was difficult for the remaining employees to ensure optimal work
conditions. Some had reactions to higher job demands, as showed in Liao’s
Weibo, where, after the collective turnover event, one remaining top manager
stated he was in “work overtime” mode for that month.
Changes in job demands have physiological and attitudinal effects, including
employee burnout (Cordes and Dougherty, 1993) and decline in satisfaction.
Furthermore, employees are also likely to have less time to engage in social or
citizenship activities (Podsakoff, Blume, Whiting and Podsakoff, 2009), resulting
in more negative interactions with co-workers and customers (Jackson and
Schuler, 1983), a decrease in unit cohesiveness that may further be associated
with reduced performance (Reilly et al., 2014) and increased turnover intentions
(Chen et al., 2011).
When the Qidian founders left the organization, the remaining employees had
higher job demands than normal, and the remaining managers and editors were
unable to respond to and address the demands of other employees, novel writers
and customers (readers). Also, the direct effect of the editors’ turnover is the
break in the “editor-writers” linkage. To keep important or famous novel writers,
the remaining editors had to prioritize repairing the linkages with higher level
writers, which resulted in less time to take care of the relationship with general
writers, so that service quality was impacted.
4.2.2
Proximal Outcomes: Dissatisfaction, Joint Flow, Productivity Decline
After the departure, as service quality declined, the remaining employees were
unable to focus on all situations and support all the writers in time, thus resulting
in greater writer and customer dissatisfaction.
Because of the editor—writer relationship, various writers followed editors in
leaving Qidian, with some writers hesitant to stay. When Chuangshi Literature
was founded, it had several star writers and hundreds of signed writers, showing
the influence of editors on writers. Someone concerned with the collective
turnover counted the number of job-hopping writers not including “writers for
the female channel, pen name was too popular to confirm, writers with works of
136
less than 1 million words (except outstanding writers).” It showed that at least
175 writers followed editors in leaving Qidian within half a year. According to
Sky-crane (苍天白鹤), a star writer who followed the exodus, “There are many
writers, including a number of famous writers, communicating and negotiating
with Chuangshi, but limited by contract, some of them can’t leave Qidian right
away.”
Some writers still insist that Qidian is the online literature industry’s leading
site, with the ability to “create stars.” Most of the star writers on other literature
websites were hired from Qidian. For example:
“As a writer, you work together with your editor for a long time. There will be a
tacit understanding between them, sometimes they (editor and writer) are so
close even like a couple, so it’s not an easy parting.”
—Sky-crane, a former Qidian golden star writer
“The relation between writer and editor is similar to artist and broker, as a
witness, partner, and mentor to the writer’s growth path, the editor’ s suggestions
and mobility have a great influence on writers.”
—Online literature industry worker
A “basic fact” is that writers’ productivity on Qidian significantly declined
after the turnover. The quantity of some writers’ updates decreased and some
writers’ work ended abruptly, thus resulting in reader dissatisfaction. For the
online literature industry, readers’ subscription fees are the main source of the
profit. If readers’ follow the flight of key writers, it causes a reduction in website
traffic, and therefore profit decline.
4.2.3
Distal Outcomes: Organizational Change
Collective turnover in a particular context, for instance, the departure of a large
quantity and high quality of key employees, or in this case, a founders’ group
turnover, generally means a major specific episode or crisis. As a result, the
organization will face episodic and radical change (Plowman, Baker, Beck, et al.,
2007). The interactions of actors amplify the change and simultaneously
highlights the need for a major replacement and acts as a force for restabilizing
137
the system. When systems experience major stress, larger interventions and
radical replacements are required (Weick and Quinn, 1999) to overcome major
inertia and take the form of a dramatic, frame-bending change, such as a new
strategy, structure, or top management (Romanelli and Tushman, 1994).
Organizational routines involve the coordination of multiple organizational
participants (Stene, 1940). The involvement of multiple participants ensures that
the ostensive aspect of a routine-its structural aspect —cannot be monolithic or
undifferentiated. Collective turnover behavior breaks organizational routines and
impacts organizational structure. The actions of multiple participants such as
other or replacement employees have an effect on the structures, through the
creation, maintenance, and modification of organizational routines (Feldman and
Pentland, 2003). In this case, after the departure, the institution, structure and
strategy of the Shanda Literature Group and Qidian changed.
The founders’ collective turnover event exposed Qidian to a greater volatility
and disruption and required radical replacements for restabilizing the system.
Aside from the change in top management team members mentioned above,
Qidian also adjusted the writers’ charging and benefit system3 to ensure the
retention of their most important asset, the novel writers. Two factors forced the
adjustment. (1)Writers. Writers following the exiting editors after the event
gained more external opportunities, and negotiating for more power, facilitated
the adjustment. (2) The departing group. As the departing group designed the
rules of the online literature industry, they had pioneering relevant knowledge
3
It examines two very different approaches to generating income from fan-created works in
Chinese online literature: The “freemium” model and the “pirate” approach. The “freemium”
model being applied by Shanda Literature provides users with some content for free, but
charges for the most desirable versions of its products (Xiang et al., 2012). Qidan’s Business
Model could be recaped as: the Qidian model allows writers to submit stories that readers can
download for free—at least at first. But if the stories become popular, the authors can become
a VIP member and start charging for their work. When this happens, “readers are charged 2
fen for each 1,000 words of a story they read (1 fen = 1/100th of 1 yuan). Readers can
download part of a story for free and then pay for the rest in installments once they reach a
certain point. (One yuan = approximately $0.16). 70% of the money goes to the writer—the
rest goes to Qidian. So while the price for readers is next to nothing and just a few yuan for a
full-length book, royalties can add up quickly for writers if they are able to capture a large
audience. There is also a bonus system that can earn writers even more money. Each month,
VIP members can vote on their favorite novels—the winning authors then earn bonuses of up
to 10,000 yuan. There is even a “tipping” system that allows VIPs to either give writers extra
money directly or buy votes for them. (cited from: http://publishingperspectives.com/2013/
06/scandal-rocks-chinas-largest-online-literature-site/#.VpYPoJ7KSKI)
138
about the technology and market, so it was easier for them to rebuild a similar
organization to compete with the incumbent company, and attract more writers.
To cope with these pressures, Shanda and Qidian reestablished a writers’ benefit
system to retain writers, and to increase the difficulty for the departing group to
enter the market, which also further promoted changes in the industry.
The Shanda Literature Group also implemented structural change. As Qidian’s
investor, Shanda attempted to gain control rights by hiring professional managers
and building Yuncheng, while in reality the founders of Qidian controlled it. As
the control conflict between the founders and the investor accumulated, the
collective turnover event provided an opportunity for Shanda to implement
structural integration. They integrated Yuncheng and Qidian, and restructured the
development strategy.
Proposition 5. Collective turnover will directly influence operational
performance, and is positively relevant to the increase in employees’ job
demands, operations disruption, and decline in service quality.
Proposition 6. Collective turnover will indirectly influence customer satisfaction.
An increase in job demands, operations disruption, and decline in service quality
will mediate the collective turnover—customer satisfaction relationship.
Proposition 7. Collective turnover has a positive effect on organizational change,
including changes in top managers, structure, institutional and strategic change.
4.3
Effect on Financial Performance
Collective turnover has an effect on market and financial performance. In this
case, the collective turnover of the founders of Qidian, influenced Shanda
Literature’s market share and financial performance.
The financial performance effects chain follows four paths. The first path is
“collective turnoverÆhuman capital flowÆintellectual assets shrinkage.”
Human capital resource depletion will lead to organizational human capital and
social capital loss, and replacement usually cannot fully compensate the loss,
which means intellectual assets shrink for the organization. The second path is
“collective turnoverÆknowledge spilloverÆintangible assets shrinkage.” The
new entrants can transfer knowledge through inheritance, which decreases the
resource value of incumbent knowledge. The third path is “collective
139
turnoverÆcustomers, partner joint flowÆmarket share shrinkage.” The joint
mobility of suppliers and customers after collective turnover, will mediate
collective turnover-market performance. The fourth path is “collective
turnoverÆhuman
capital
flowÆoperational
performanceÆfinancial
performance.” Collective turnover will have a negative effect on operational
performance, includes proximal outcome (e.g., operation disruptions and decline
in service quality and productivity) and distal outcomes (e.g., organizational
change), and collective turnover will indirectly influence financial performance
through operational performance. In this case, collective turnover had an impact
on operational performance, causing a decline in writers’ productivity and
website traffic and a withdrawn IPO. In the long term it led to the shrinkage of
Shanda Literature valuation and a loss of market share.
Figure 2 Qidian Traffic Trends
Notes. (1) Reach percentage per day = Unique visitors per day to focus website/ Unique visitors per day to
all websites. (2) The dashed lines indicate the linear trends.
Data source: iUserTracker vertical literature website monitors data, collected through long-term
monitoring of 400,000 home and office samples (without public internet access) of internet behavior. The
number in 2011 and 2014 is calculated over a 12-month average, the number in 2012 is calculated over a
9-month average (not including September, November and December), the number in 2013 is calculated
over a 7-month average (not including January, March, April, May, June, as iUserTracker does not report
that data).
According to vertical literature website data from iResearch’s (艾瑞咨询 )
140
iUserTracker system,4 we draw a Qidian website traffic trend in Figure 2. The
Figure 2 shows that there is a decreasing trend of unique visitors to Qidian per
day, partially because of the development of mobile internet--which caused users
to shift from personal computers to mobile terminals. In 2011, the unique visitors
per day was 2.56 million. It decreased by 12.3%, .32 million in 2012, but by
2013, the number was 1.84 million, with a fall of 17.9%. The number indicates a
sharp drop in the year when collective turnover happen. Qidian’s reach
percentage per day is still No.1, but on a decreasing trend, as fierce competition
has resulted in a decline in market share.
Collective turnover has become the impetus for industry change. The departing
group received investment from Tencent, integrated Tencent Literature and
launched Chuangshi (创世中文网). The internet giant Baidu entered into the
online literary market by acquiring all shares in 91 Panda Reading mobile app
(91 熊猫看书) and Zongheng Literature (www.zongheng.com). These, as well as
other mergers and acquisitions in the industry have caused Shanda Literature’s
market share to shrink. According to the “China Online Literature Industry
Research in 2013” released by Enfodesk (易观智库, www.analysys.cn), The
Chinese online literature industry structure was dominating by ChineseAll (中文
在线, www.chineseall.com) represented by 17K (17K 小说网), Shanda Literature
represented by Qidian, and Tencent Literature represented by Chuangshi as of the
end of 2013. Turbulence caused by collective turnover, provided an opportunity
for these rivals to gain markets shares.
Proposition 8. Collective turnover will indirectly influence financial
performance. Human capital flow and operational performance mediate the
collective turnover—financial performance relationship.
5
Holistic Theory Model: Consequences of Collective
Turnover
Based on the above analysis, we show the model of the consequences of
collective turnover theory in Figure 3. Similar to event chain theory, the
collective turnover effects chain also includes three elements: context, episodes
and objects.
4
http://report.iresearch.cn/data.shtml
141
Figure 3 Consequences of Collective Turnover Theory Model
Notes. The dashed frame shows the antecedents of relevant effects, but not the variable of operational
performance or financial performance.
Collective turnover has a cascade effect. Whether or not it will cause a series
of secondary and derivative events is determined by context factors such as
climate, industry features, and environmental complexity. For instance, in this
case study, the consequences of collective turnover was influenced by the
142
atmosphere at Qidian, the maturity of the online literature industry, the
development stage of the online literature industry, interactions between Qidian,
the group departing and other actors. Therefore, context factors are important
elements in predicting the consequences of collective turnover. We need to pay
more attention to context elements, and a detailed exploration of the context
effect mechanism is still required.
The consequences of collective turnover also concern temporal dynamics.
Based on this case study, we determine three main consequence chains: the
human capital flow chain, the effect on operational performance chain and the
effect on financial performance chain, and these three aspects will influence or be
influenced by each other. Collective turnover will directly influence human
capital flow, human capital flow has an effect on operational performance, and
human capital and operational performance both impact financial performance.
The consequences of collective turnover is temporally dynamic and complicated.
There are a variety of objects that will be influenced by collective turnover,
including the original organization, the departing group, intervenor in the
collective turnover event, and other stakeholders such as the remaining
employees, cooperators, rivals and customers.
6
Discussion
6.1
Contribution
First, a new perspective to explain collective turnover is used, and contributes to
the extension of collective turnover theory and organizational behavior theory.
Based on a longitudinal single case study, we develop a holistic theory model of
the consequences of collective turnover and explore the causal logic chain of
developing consequences. By integrating existing studies and a longitudinal
analysis, we develop a theory framework to explain what and how collective
turnover will influence. Incorporating context and time, it has a dynamic and
cascading effect and causes a series of secondary and derivative events. Three
main effect chains are identified—both proximal and distal impacts on human
capital flow, operational performance and financial performance. This provides a
holistic perspective to understand the chain effects of collective turnover.
Second, we posit that whether collective turnover has a positive or negative
effect depends on the context factors. The industry environment and industry
143
boundary will enlarge or diminish the consequences of collective turnover. By
examining the potential for the positive consequences of collective turnover,
group departure causes position vacancies, which may provide promotion
opportunities for remaining employees, or external recruitment will bring new
changes or create an opportunity to learn new knowledge. As well, collective
turnover is related to organizational change. Depending on the specific context,
collective turnover may produce positive or negative effects on performance. For
instance, Karim and Kaul’s (2015) study suggests that structural recombination
will have a positive effect on firm innovation where there is unexploited
relatedness between the firm’s knowledge resources, and where the firm has high
quality, general purpose knowledge. This suggests that we should explore the
consequences of collective turnover taking contextual factors into consideration.
Third, a longitude single case study provides detailed information about
collective turnover, for a comprehensive estimate of the collective turnover
effects, which expands our ability to explore collective turnover consequences in
ways that have not been fully recognized. CET theory introduced by Nyberg and
Ployhart (2013) provides a framework for theorizing about collective turnover,
with a focus on human capital resource depletion. Compared with CET theory,
collective turnover consequences chain theory focuses on the effects caused by
collective turnover, and we explore the complicated effects of collective turnover
caused by the interactions among leavers, human capital losing firms, rival firms,
and other actors in the organizational field, and the context within which they
interact. It is our hope that the consequences of collective turnover theory
facilitates a greater understanding of this important organizational phenomenon.
6.2
Directions for Future Research
What factors determine whether or not collective turnover will have powerful
effects? We chose a case with extreme circumstances, which have had a powerful
influence, but not all collective turnover cases have such enormous effects.
Adapting the earthquake metaphor, an earthquake of magnitude 7.0 releases 32
times as much energy as an earthquake measuring 6.0, so the differences in
specific collective turnover consequences in various contexts should also be
explored. Climate, industry characteristics, and environmental complexity may
be important relevant factors, but this still needs to be proven.
144
Conceptual and empirical investigations are also needed to clarify the
collective turnover—consequence (e.g., human capital flow, operational
performance) relationships. Collective turnover is primarily measured using rates.
Alternative measures may be preferred, and some researchers suggest
considering collective turnover in terms of the departing group’s characteristics
(e.g., quantity and quality). Considering the temporal dynamics of collective
turnover, proper approaches also need to be chosen.
Collective turnover has multi-level consequences. In this research, we build a
holistic theory model for the effects on the original organization, that is, the
organization that needs to deal with human capital resource depletion. The
impacts on leavers or the recipient organization and industry have received little
attention. In future research, there should be a more fine-grained consideration of
collective turnover effects on industry evolution, new industry, and recipient
organizations.
Acknowledgements The study is supported by China’s National Nature Science Foundation
(No. 71472094, 71132001). We gratefully acknowledge the invaluable comments and advice
from Professor Bing Ren (任兵). We thank the editors and two anonymous reviewers for their
constructive and generative comments throughout the review process.
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- Frontiers of Business Research in China

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