LOS ANÁLISIS DE LOS ESTUDIOS DE SEGUIMIENTO, CORROBORADOS POR LOS DATOS SOBRE LAS VENTAS AL POR MAYOR Y AL POR MENOR, CONFIRMAN QUE LAS

Despite  having  a  long-­‐standing  place  in  research  (Emery  and  Trist,  1965),  turbulence,   the  third  main  literature  theme  reviewed,  is  the  least  defined.    Within  both  subsets   of  this  theme—task  environment  and  chaos  and  complexity  theory—there  is  a   narrow  set  of  frequently  referenced  studies.    

2.11.4.1.  Task  Environment  

Task  environment  can  be  conceptualized  as  the  relative  ease  with  which  an   organization  can  accomplish  its  goals  through  receipt  of  the  resources  it  needs  to   accomplish  them.    Thus,  task  environments  can  vary  in  terms  of  complexity   (simplicity)  as  well  as  hostility  (munificence).    The  papers  discussed  in  the  task   environment  subset  all  concern  conditions  of  variation  within  the  task  environment,   although  at  times  indirectly.  

The  first  study  reviewed  in  this  subset  is  Lawrence  and  Lorsch’s  (1967)  classic  study   of  six  chemical  processing  companies.    They  found  that  in  dynamic  environments   organizations  must  be  able  to  manage  a  range  of  differentiating  and  integrating   variables  that  at  times  conflict.    To  successfully  manage  this  complexity,  

organizations  must  develop  the  capability  to  manage  high  levels  of  differentiation   while  maintaining  a  high  degree  of  integration.    Organizations  use  integrative   devices  to  accomplish  this—some  more  successfully  than  others.  

Thompson  (1967)  provides  an  early  yet  surprisingly  concise  and  comprehensive   analysis  of  organizations  in  his  book  Organizations  in  Action.  The  book  provides   insights  into  organizational  types,  strategies,  and  forms  of  control,  and  is  replete   with  propositions  that  are  presented  and  addressed  with  organizational  literature   existing  at  the  time.    Useful  specifically  are  the  variables  discussed  that  contribute  to   organizational  uncertainty—two  external  and  one  internal:  general  uncertainty,   contingency,  and  interdependence  of  components  (Thompson,  1967,  p.  159).    

Dess  and  Beard  (1984),  aggregating  Aldrich’s  (1979)  six  environmental  dimensions,   identified  three  dimensions  that  can  be  used  to  assess  task  environments:    

munificence,  dynamism,  and  complexity.    Their  analysis  of  52  manufacturing  

industries  showed  that  multiple  underlying  variables  could  be  loaded  onto  the  three   variables,  thus  providing  a  straightforward  way  in  which  to  assess  the  characteristics   of  the  task  environment.    The  variables  are  used  extensively  in  subsequent  empirical  

Edward  A.  Barrows,  Jr.  –  Cranfield  University  –  School  of  Management  –  DBA  Thesis   How  Firms  in  Turbulent  Environments  Measure  Strategic  Performance  

127  

research  presumably  because  of  their  ease  of  use  and  validity.    Harris  (2004)  

reexamined  the  convergent  and  discriminant  validity  of  the  variables,  using  a  larger   sample  size  of  247  organizations  and  the  more  sophisticated  method  of  structural   equation  modeling.    He  concluded  that  the  Dess  and  Beard  (1984)  variables  have   construct  but  not  discriminant  validity.    Further,  he  recommends  researchers  revert   to  the  six  Aldrich  variables  or  seek  to  identify  another  theoretical  framework  all   together.      

2.11.4.2.  Chaos  and  Complexity  

Complexity  theory  is  growing  in  use  in  management  research.    Several  researchers   (Cunha  and  Cunha,  2006;  Davis  et  al.,  2009)  have  recently  begun  to  establish  its  use   as  a  viable  theoretical  paradigm  to  describe  rapidly  changing  or  dynamic  

environments.    Levy  (1994)  examined  chaos  and  complexity  with  a  supply  chain   simulation  and  concluded  from  his  analysis  that  industries  behave  like  complex   adaptive  systems.    Since  change  can  happen  unexpectedly,  accurate  forecasting  is   virtually  impossible,  so  organizations  operating  within  these  contexts  must  become   adaptive  and  flexible  in  order  to  survive.  

Levy’s  views  were  advanced  and  strengthened  by  case-­‐study  research  conducted  by   Brown  and  Eisenhardt  (1997),  who  analyzed  six  firms  in  the  technology  industry.     Their  starting  point  was  the  premise  that  organizations  no  longer  exist  in  an  

environment  of  punctuated  equilibrium;  rather,  they  operate  in  a  state  of  constant   change—whether  it  be  incremental  or  radical.    As  such,  traditional  theories  such  as   transaction  cost  economics  and  agency  theory—theories  developed  in  stable   environments—are  insufficient  in  terms  of  explaining  behavior  and  performance   (Brown  and  Eisenhardt,  1997,  p.  3).    They  conclude  that  effective  organizations— those  that  survive  and  adapt  in  these  types  of  environments—create  temporary   semi-­‐structures  to  aid  in  the  management  of  the  organization  as  well  as  links  that   connect  existing  work  to  probes  or  tests  of  new  opportunities.      

Anderson  (1999)  wrote  a  conceptual  paper  elaborating  the  specific  elements  of   complexity  theory  while  at  the  same  time  demonstrating  its  relevancy  to  

organizational  studies.    The  paper  has  become  a  mainstay  in  research  conducted   with  complexity  theory,  since  it  clearly  specifies  how  complex,  adaptive,  non-­‐linear   thinking  can  be  incorporated  into  both  management  practice  and  research.    At  the   same  time,  several  articles  published  in  the  Sloan  Management  Review  elaborated   on  the  complexity  concepts  discussed  by  Anderson  and  showed  how  they  were  

Edward  A.  Barrows,  Jr.  –  Cranfield  University  –  School  of  Management  –  DBA  Thesis   How  Firms  in  Turbulent  Environments  Measure  Strategic  Performance  

128  

applied  in  actual,  versus  speculated,  practice.    Pascale  (1999)  put  complexity  theory   into  more  practical  terms  than  Anderson  by  discussing  Shell’s  efforts  to  disturb   equilibrium.    Beinhocker  (1999)  suggested  the  creation  of  “robust,  adaptive  

strategies”—similar  to  Brown  and  Eisenhardt’s  (1997)  semi-­‐structures—and  the  use   of  “adaptive  walks”  to  explore  different  elements  of  the  shifting  competitive  

landscape.    

More  recently  and  specifically,  Meade  et  al.  (2006)  apply  both  chaos  and  complexity   theories  to  technology  adoption.    In  their  study  of  the  hard-­‐drive,  microprocessor,   and  semiconductor  industries—done  by  examining  total  market  share/product  sales   over  time—they  show  how  a  complexity  theory  model  called  Adopter  Framework  is   able  to  predict  technology  adoption  rates  over  time  and  conclude  by  saying  that  it  is   likely  the  framework  can  be  used  in  other  examples.